Sukumaran, R. | bioRxiv Science

bioRxiv2022

RADGENNETS: DEEP LEARNING-BASED RADIOGENOMICS MODEL FOR GENE MUTATION PREDICTION IN LUNG CANCER

AO_SCPLOWBSTRACTC_SCPLOWIn this paper, we present our methodology that can be used for predicting gene mutation in patients with non-small cell lung cancer (NSCLC). There are three major types of gene mutations that a NSCLC patients gene structure can change to: epidermal growth factor receptor (EGFR), Kirsten rat sarcoma virus (KRAS), and Anaplastic lymphoma kinase (ALK). We worked with the clinical and genomics data for each patient as well CT scans. We preprocessed all of the data and then built a novel pipeline to integrate both the image and tabular data. We built a novel pipeline that used a fusion of Convolutional Neural Networks and Dense Neural Networks. Also, using a search approach, we pick an ensemble of deep learning models to classify the separate gene mutations. These models include EfficientNets, SENet, and ResNeXt WSL, among others. Our model achieved a high area under curve (AUC) score of 94% in detecting gene mutation.

cancer biology↗

bioRxiv2018

Comprehensive Identification of Fim-Mediated Inversions in Uropathogenic Escherichia coli with Structural Variation Detection Using Relative Entropy

Most urinary tract infections (UTIs) are caused by uropathogenic Escherichia coli (UPEC), which depend on an extracellular organelle (Type 1 pili) for adherence to bladder cells during infection. Type 1 pilus expression is partially regulated by inversion of a piece of DNA referred to as fimS, which contains the promoter for the fim operon encoding Type 1 pili. fimS inversion is regulated by up to five recombinases collectively known as Fim recombinases. These Fim recombinases are currently known to regulate two other switches: the ipuS and hyxS switches. A long-standing question has been whether the Fim recombinases regulate the inversion of other switches, perhaps to coordinate expression for adhesion or virulence. We answered this question using whole genome sequencing with a newly developed algorithm (Structural Variation detection using Relative Entropy, SVRE) for calling structural variations using paired-end short read sequencing. SVRE identified all of the previously known switches, refining the specificity of which recombinases act at which switches. Strikingly, we found no new inversions that were mediated by the Fim recombinases. We conclude that the Fim recombinases are each highly specific for a small number of switches. We hypothesize that the unlinked Fim recombinases have been recruited to regulate fimS, and fimS only, as a secondary locus; this further implies that regulation of Type 1 pilus expression (and its role in gastrointestinal and/or genitourinary colonization) is important enough, on its own, to influence the evolution and maintenance of multiple additional genes within the accessory genome of E. coli.\n\nImportanceUTIs are a common ailment that affects more than half of all women during their lifetime. The leading cause of UTIs is UPEC, which rely on Type 1 pili to colonize and persist within the bladder during infection. The regulation of Type 1 pili is remarkable for an epigenetic mechanism in which a section of DNA containing a promoter is inverted. The inversion mechanism relies on what are thought to be dedicated recombinase genes; however, the full repertoire for these recombinases is not known. We show here that there are no additional targets beyond those already identified for the recombinases in the entire genome of two UPEC strains, arguing that Type 1 pilus expression itself is the driving evolutionary force for the presence of these recombinase genes. This further suggests that targeting the Type 1 pilus is a rational alternative non-antibiotic strategy for the treatment of UTI.

microbiology↗