Deep Learning for Subtypes Identification of Pure Seminoma of the Testis

The most critical step in the clinical diagnosis workflow is the pathological evaluation of each tumor sample. Deep learning is a powerful approach that is widely used to enhance diagnostic accuracy and streamline the diagnosis process. In our previous study using omics data, we identified 2 distinct subtypes of pure seminoma. Seminoma is the most common histological type of testicular germ cell tumors (TGCTs). Here we developed a deep learning decision making tool for the identification of seminoma subtypes using histopathological slides. We used all available slides for pure seminoma samples from The Cancer Genome Atlas (TCGA). The developed model showed an area under the ROC curve of 0.896. Our model not only confirms the presence of 2 distinct subtypes within pure seminoma but also unveils the presence of morphological differences between them that are imperceptible to the human eye

Functional analysis of Rossmann-like domains reveals convergent evolution of topology and reaction pathways.

Rossmann folds are ancient, frequently diverged domains found in many biological reaction pathways where they have adapted for different functions. Consequently, discernment and classification of their homologous relations and function can be complicated. We define a minimal Rossmann-like structure motif (RLM) that corresponds for the common core of known Rossmann domains and use this motif to identify all RLM domains in the Protein Data Bank (PDB), thus finding they constitute about 20% of all known 3D structures. The Evolutionary Classification of protein structure Domains (ECOD) classifies RLM domains in a number of groups that lack evidence for homology (X-groups), which suggests that they could have evolved independently multiple times. Closely related, homologous RLM enzyme families can diverge to bind different ligands using similar binding sites and to catalyze different reactions. Conversely, non-homologous RLM domains can converge to catalyze the same reactions or to bind the same ligand with alternate binding modes. We discuss a special case of such convergent evolution that is relevant to the polypharmacology paradigm, wherein the same drug (methotrexate) binds to multiple non-homologous RLM drug targets with different topologies. Finally, assigning proteins with RLM domain to the Enzyme Commission classification suggest that RLM enzymes function mainly in metabolism (and comprise 38% of reference metabolic pathways) and are overrepresented in extant pathways that represent ancient biosynthetic routes such as nucleotide metabolism, energy metabolism, and metabolism of amino acids. In fact, RLM enzymes take part in five out of eight enzymatic reactions of the Wood-Ljungdahl metabolic pathway thought to be used by the last universal common ancestor (LUCA). The prevalence of RLM domains in this ancient metabolism might explain their wide distribution among enzymes

Pan-cancer structurome reveals overrepresentation of beta sandwiches and underrepresentation of alpha helical domains

Abstract The recent progress in the prediction of protein structures marked a historical milestone. AlphaFold predicted 200 million protein models with an accuracy comparable to experimental methods. Protein structures are widely used to understand evolution and to identify potential drug targets for the treatment of various diseases, including cancer. Thus, these recently predicted structures might convey previously unavailable information about cancer biology. Evolutionary classification of protein domains is challenging and different approaches exist. Recently our team presented a classification of domains from human protein models released by AlphaFold. Here we evaluated the pan-cancer structurome, domains from over and under expressed proteins in 21 cancer types, using the broadest levels of the ECOD classification: the architecture (A-groups) and possible homology (X-groups) levels. Our analysis reveals that AlphaFold has greatly increased the three-dimensional structural landscape for proteins that are differentially expressed in these 21 cancer types. We show that beta sandwich domains are significantly overrepresented and alpha helical domains are significantly underrepresented in the majority of cancer types. Our data suggest that the prevalence of the beta sandwiches is due to the high levels of immunoglobulins and immunoglobulin-like domains that arise during tumor development-related inflammation. On the other hand, proteins with exclusively alpha domains are important elements of homeostasis, apoptosis and transmembrane transport. Therefore cancer cells tend to reduce representation of these proteins to promote successful oncogeneses

Pure Seminoma Subtyping Using Computational Approaches

Testicular germ cell tumors (TGCT) being the most common solid malignancy in adolescent and young men, are second in terms of the average life years lost per person dying of cancer. Two major types of TGCTs are seminoma and non-seminoma (NSE). Management of patients with seminoma includes orchiectomy, platinum-based chemotherapy or radiation therapy. Despite a high patient survival rate, current treatments significantly decrease patients’ quality of life and lead to around 40 severe side effects. We conducted a computational study of 64 pure seminomas (the most common subtype of TGCTs) available at TCGA. Consensus clustering approach of seminoma samples based on transcriptomic data identified two distinct subtypes that showed differences in pluripotency stage, activity of double stranded DNA breaks repair mechanisms, rates of loss of heterozygosity, DNA methylation, expression of lncRNA associated with cisplatin resistance and level of lymphocytes infiltration. Seminoma subtype2 shows signs of differentiation into NSE and therefore may have higher resistance to platinum-based chemotherapy. Despite of the high level of lymphocyte infiltration, TGCTs immunotherapy clinical trials were shut down due to lacking clinical efficacy. We identified 20 significantly overexpressed genes in subtype2 that are related to senescence-associated secretory phenotype. This fact and data on altered pathways in subtype2 allow us to hypothesize that senescence of seminoma infiltrating lymphocytes can be one of the reasons for immunotherapy failure. Using all available histopathological slides of pure seminoma at TCGA we developed test version of deep learning (DL) decision making tool for identification of seminoma subtypes using only slide images (accuracy 0.864). As future direction we plan to develop DL tool for identification of seminoma subtypes using whole slide images (WSI). This approach will simplify utilization of this tool by pathologists but also requires significantly more powerful computational resources and we anticipate to use TACC resources for this task.Texas Advanced Computing Center (TACC

High temperature and pressure influence the interdomain orientation of Nip7 proteins from <i>P. abyssi</i> and <i>P. furiosus</i>: MD simulations

<p>Interactions between protein domains and their position and movement relative to each other are essential for the stability and normal functioning of a protein molecule. Features of the movement of domains may define the mechanism of enzymatic reactions. Therefore, the description of this motion is an important task in the analysis of the structures and functions of multidomain proteins. In the current work, we investigated the influence of pressure and temperature on changes in the movement of the two domains of the protein Nip7, expressed by deep-water (<i>Pyrococcus abyssi</i>) and shallow-water (<i>Pyrococcus furiosus</i>) archaea. The results of the present study show that the interdomain interfaces of the Nip7 proteins of <i>P. abyssi</i> and <i>P. furiosus</i> are formed by stable hydrophobic interactions. It was shown that high pressure and high temperature significantly changed the orientation of domains in Nip7 proteins which perhaps was connected with functional features of these domains. It was found that increasing the pressure significantly changed the angle of rotation of these domains, to a greater extent in the shallow-water protein, while an increase in temperature slightly reduced the angle of rotation of these domains. Moreover, the results suggest that the type of motion of the domains under study is similar to shear motion.</p