Pirh2-dependent DNA damage in neurons induced by the G-quadruplex ligand pyridostatin.

Noncanonical base pairing between four guanines (G) within single-stranded G-rich sequences leads to formation of а G-quartet. Self-stacking of G-quartets results in a columnar four-stranded DNA structure known as the G-quadruplex (G4 or G4-DNA). In cancer cells, G4-DNA regulates multiple DNA-dependent processes, including transcription, replication, and telomere function. How G4s function in neurons is poorly understood. Here, we performed a genome-wide gene expression analysis (RNA-Seq) to identify genes modulated by a G4-DNA ligand, pyridostatin (PDS), in primary cultured neurons. PDS promotes stabilization of G4 structures, thus allowing us to define genes directly or indirectly responsive to G4 regulation. We found that 901 genes were differentially expressed in neurons treated with PDS out of a total of 18,745 genes with measured expression. Of these, 505 genes were downregulated and 396 genes were upregulated and included gene networks regulating p53 signaling, the immune response, learning and memory, and cellular senescence. Within the p53 network, the E3 ubiquitin ligase Pirh2 (Rchy1), a modulator of DNA damage responses, was upregulated by PDS. Ectopically overexpressing Pirh2 promoted the formation of DNA double-strand breaks, suggesting a new DNA damage mechanism in neurons that is regulated by G4 stabilization. Pirh2 downregulated DDX21, an RNA helicase that unfolds G4-RNA and R-loops. Finally, we demonstrated that Pirh2 increased G4-DNA levels in the neuronal nucleolus. Our data reveal the genes that are responsive to PDS treatment and suggest similar transcriptional regulation by endogenous G4-DNA ligands. They also connect G4-dependent regulation of transcription and DNA damage mechanisms in neuronal cells.

Efficient quality control of whole slide pathology images with human-in-the-loop training.

Histopathology whole slide images (WSIs) are being widely used to develop deep learning-based diagnostic solutions, especially for precision oncology. Most of these diagnostic softwares are vulnerable to biases and impurities in the training and test data which can lead to inaccurate diagnoses. For instance, WSIs contain multiple types of tissue regions, at least some of which might not be relevant to the diagnosis. We introduce HistoROI, a robust yet lightweight deep learning-based classifier to segregate WSI into 6 broad tissue regions-epithelium, stroma, lymphocytes, adipose, artifacts, and miscellaneous. HistoROI is trained using a novel human in-the-loop and active learning paradigm that ensures variations in training data for labeling efficient generalization. HistoROI consistently performs well across multiple organs, despite being trained on only a single dataset, demonstrating strong generalization. Further, we have examined the utility of HistoROI in improving the performance of downstream deep learning-based tasks using the CAMELYON breast cancer lymph node and TCGA lung cancer datasets. For the former dataset, the area under the receiver operating characteristic curve (AUC) for metastasis versus normal tissue of a neural network trained using weakly supervised learning increased from 0.88 to 0.92 by filtering the data using HistoROI. Similarly, the AUC increased from 0.88 to 0.93 for the classification between adenocarcinoma and squamous cell carcinoma on the lung cancer dataset. We also found that the performance of the HistoROI improves upon HistoQC for artifact detection on a test dataset of 93 annotated WSIs. The limitations of the proposed model are analyzed, and potential extensions are also discussed.

The Tardigrade damage suppressor protein Dsup promotes DNA damage in neurons.

Tardigrades are microscopic invertebrates, which are capable of withstanding extreme environmental conditions, including high levels of radiation. A Tardigrade protein, Dsup (Damage Suppressor), protects the Tardigrade's DNA during harsh environmental stress and X-rays. When expressed in cancer cells, Dsup protects DNA from single- and double-strand breaks (DSBs) induced by radiation, increases survival of irradiated cells, and protects DNA from reactive oxygen species. These unusual properties of Dsup suggested that understanding how the protein functions may help in the design of small molecules that could protect humans during radiotherapy or space travel. Here, we investigated if Dsup is protective in cortical neurons cultured from rat embryos. We discovered that, in cortical neurons, the codon-optimized Dsup localizes to the nucleus and, surprisingly, promotes neurotoxicity, leading to neurodegeneration. Unexpectedly, we found that Dsup expression results in the formation of DNA DSBs in cultured neurons. With electron microscopy, we discovered that Dsup promotes chromatin condensation. Unlike Dsup's protective properties in cancerous cells, in neurons, Dsup promotes neurotoxicity, induces DNA damage, and rearranges chromatin. Neurons are sensitive to Dsup, and Dsup is a doubtful surrogate for DNA protection in neuronal cells.

Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program.

Type 1 and Type 2 diabetes are distinct genetic diseases of the pancreas which are defined by the abnormal level of blood glucose. Understanding the initial molecular perturbations that occur during the pathogenesis of diabetes is of critical importance in understanding these disorders. The inability to biopsy the human pancreas of living donors hampers insights into early detection, as the majority of diabetes studies have been performed on peripheral leukocytes from the blood, which is not the site of pathogenesis. Therefore, efforts have been made by various teams including the Human Pancreas Analysis Program (HPAP) to collect pancreatic tissues from deceased organ donors with different clinical phenotypes. HPAP is designed to define the molecular pathogenesis of islet dysfunction by generating detailed datasets of functional, cellular, and molecular information in pancreatic tissues of clinically well-defined organ donors with Type 1 and Type 2 diabetes. Moreover, data generated by HPAP continously become available through a centralized database, PANC-DB, thus enabling the diabetes research community to access these multi-dimensional data prepublication. Here, we present the computational workflow for single-cell RNA-seq data analysis of 258,379 high-quality cells from the pancreatic islets of 67 human donors generated by HPAP, the largest existing scRNA-seq dataset of human pancreatic tissues. We report various computational steps including preprocessing, doublet removal, clustering and cell type annotation across single-cell RNA-seq data from islets of four distintct classes of organ donors, i.e. non-diabetic control, autoantibody positive but normoglycemic, Type 1 diabetic, and Type 2 diabetic individuals. Moreover, we present an interactive tool, called CellxGene developed by the Chan Zuckerberg initiative, to navigate these high-dimensional datasets. Our data and interactive tools provide a reliable reference for singlecell pancreatic islet biology studies, especially diabetes-related conditions.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Role of Stress-Survival Pathways and Transcriptomic Alterations in Progression of Colorectal Cancer: A Health Disparities Perspective.

Every year, more than a million individuals are diagnosed with colorectal cancer (CRC) across the world. Certain lifestyle and genetic factors are known to drive the high incidence and mortality rates in some groups of individuals. The presence of enormous amounts of reactive oxygen species is implicated for the on-set and carcinogenesis, and oxidant scavengers are thought to be important in CRC therapy. In this review, we focus on the ethnicity-based CRC disparities in the U.S., the negative effects of oxidative stress and apoptosis, and gene regulation in CRC carcinogenesis. We also highlight the use of antioxidants for CRC treatment, along with screening for certain regulatory genetic elements and oxidative stress indicators as potential biomarkers to determine the CRC risk and progression.

Identification of Hub Genes in Different Stages of Colorectal Cancer through an Integrated Bioinformatics Approach.

Colorectal cancer (CRC) is the third most common cancer that contributes to cancer-related morbidity. However, the differential expression of genes in different phases of CRC is largely unknown. Moreover, very little is known about the role of stress-survival pathways in CRC. We sought to discover the hub genes and identify their roles in several key pathways, including oxidative stress and apoptosis in the different stages of CRC. To identify the hub genes that may be involved in the different stages of CRC, gene expression datasets were obtained from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) common among the different datasets for each group were obtained using the robust rank aggregation method. Then, gene enrichment analysis was carried out with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Finally, the protein-protein interaction networks were constructed using the Cytoscape software. We identified 40 hub genes and performed enrichment analysis for each group. We also used the Oncomine database to identify the DEGs related to stress-survival and apoptosis pathways involved in different stages of CRC. In conclusion, the hub genes were found to be enriched in several key pathways, including the cell cycle and p53 signaling pathway. Some of the hub genes were also reported in the stress-survival and apoptosis pathways. The hub DEGs revealed from our study may be used as biomarkers and may explain CRC development and progression mechanisms.

Mucopyocele of the maxillary sinus.

Mucoceles are defined as chronic, cystic lesions in the paranasal sinuses. When the mucocele content becomes infected, the lesion is defined as mucopyocele. Most mucoceles are located in the frontal and anterior ethmoid sinuses and normally they involve the frontal-ethmoid complex, expanding to the superior-medial region of the orbit, leading to ocular disorders; maxillary sinus presentation is rare. In the present article, the authors described a rare case of mucopyocele in the maxillary sinus.

In silico model for P-glycoprotein substrate prediction: insights from molecular dynamics and in vitro studies.

P-glycoprotein (P-gp) is a plasma membrane efflux transporter belonging to ATP-binding cassette superfamily, responsible for multidrug resistance in tumor cells. Over-expression of P-gp in cancer cells limits the efficacy of many anticancer drugs. A clear understanding of P-gp substrate binding will be advantageous in early drug discovery process. However, substrate poly-specificity of P-gp is a limiting factor in rational drug design. In this investigation, we report a dynamic trans-membrane model of P-gp that accurately identified the substrate binding residues of known anticancer agents. The study included homology modeling of human P-gp based on the crystal structure of C. elegans P-gp, molecular docking, molecular dynamics analyses and binding free energy calculations. The model was further utilized to speculate substrate propensity of in-house anticancer compounds. The model demonstrated promising results with one anticancer compound (NSC745689). As per our observations, the molecule could be a potential lead for anticancer agents devoid of P-gp mediated multiple drug resistance. The in silico results were further validated experimentally using Caco-2 cell lines studies, where NSC745689 exhibited poor permeability (P app 1.03 ± 0.16 × 10(-6) cm/s) and low efflux ratio of 0.26.

Left renal hydatid cyst presenting as hematuria and macroscopic hydatiduria since last ten years.

Renal hydatidosis represents only 2-3% of hydatid disease. It is endemic in parts of eastern Europe, middle East, south America, Australia, New Zealand, Alaska, and Canada. Cystic rupture into the collecting system causes hydaturia; isolated renal involvement is even rarer. Here we report a case of left renal hydatid cyst in a 40 year old man presenting as hematuria and macroscopic hydaturia since last ten years. The patient underwent exploratory laparotomy and recovered.

Acute presentation of a benign cystadenofibroma of the fallopian tube: a case report.

INTRODUCTION: Cystadenofibromas are rare benign tumors of the fallopian tube with only 15 reported cases worldwide. They are usually asymptomatic and are found incidentally. This case is presented on account of its rarity and to the best of our knowledge, is the first reported case of cystadenofibroma of the fallopian tube discovered during an appendicectomy. CASE PRESENTATION: We report a rare case of cystadenofibroma of the fallopian tube in a 19-year-old Caucasian woman who presented with sudden onset of right iliac fossa pain. A clinical diagnosis of appendicitis was made and she was taken to the operating theater for an appendicectomy. Intraoperatively, the appendix appeared normal. However, the 8 cm cyst contained within the right ovary and the blood in the pelvis warranted a salpingo-oopherectomy. Our patient made an uneventful recovery and was discharged after four days. Histology revealed a benign cystadenofibroma of the fallopian tube. There was no evidence of recurrence in the follow-up period of 12 months. CONCLUSION: Cystadenofibromas are benign tumors that may macroscopically and ultrasonographically appear malignant. We recommend that the diagnosis of cystadenofibroma is considered prior to performing radical surgery that may affect the fecundity of these patients. Cystadenofibromas confined to the fallopian tube can be treated curatively with unilateral salpingo-oophorectomy, without the need for any further treatment. However, long-term follow-up of more cases is required to draw more definitive conclusions.