Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.

The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.

PDBminer to Find and Annotate Protein Structures for Computational Analysis.

Computational methods relying on protein structure strongly depend on the structure selected for investigation. Typical sources of protein structures include experimental structures available at the Protein Data Bank (PDB) and high-quality in silico model structures, such as those available at the AlphaFold Protein Structure Database. Either option has significant advantages and drawbacks, and exploring the wealth of available structures to identify the most suitable ones for specific applications can be a daunting task. We provide an open-source software package, PDBminer, with the purpose of making structure identification and selection easier, faster, and less error prone. PDBminer searches the AlphaFold Database and the PDB for available structures of interest and provides an up-to-date, quality-ranked table of structures applicable for further use. PDBminer provides an overview of the available protein structures to one or more input proteins, parallelizing the runs if multiple cores are specified. The output table reports the coverage of the protein structures aligned to the UniProt sequence, overcoming numbering differences in PDB structures and providing information regarding model quality, protein complexes, ligands, and nucleic acid chain binding. The PDBminer2coverage and PDBminer2network tools assist in visualizing the results. PDBminer can be applied to overcome the tedious task of choosing a PDB structure without losing the wealth of additional information available in the PDB. Here, we showcase the main functionalities of the package on the p53 tumor suppressor protein. The package is available at http://github.com/ELELAB/PDBminer.

Disseminated Mycobacterium genavense infection in a patient with a history of sarcoidosis.

We present a case of Mycobacterium genavense infection in a man in his 60s with a history of sarcoidosis, treated for 24 years with systemic corticosteroids and later methotrexate as monotherapy. He presented with low grade fever, dyspnoea and right-sided thoracic pain and was admitted due to a treatment-refractory infection. After a prolonged period of symptoms and diagnostics, acid-fast bacilli were demonstrated in pleural fluid and PCR revealed M. genavense The patient was treated with intravenous amikacin, peroral azithromycin, rifampicin and ethambutol for a total of 18 months, with a good clinical and radiological treatment response. Infection with M. genavense is rare in HIV-negative immunocompromised hosts. Diagnosing and treating mycobacterial infections, especially for more rare species, remains a challenge as clinical evidence is sparse. Nonetheless, the disease-causing infection must be considered in symptomatic and immunocompromised patients.

TRAP1 S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins.

S-nitrosylation is a post-translational modification in which nitric oxide (NO) binds to the thiol group of cysteine, generating an S-nitrosothiol (SNO) adduct. S-nitrosylation has different physiological roles, and its alteration has also been linked to a growing list of pathologies, including cancer. SNO can affect the function and stability of different proteins, such as the mitochondrial chaperone TRAP1. Interestingly, the SNO site (C501) of TRAP1 is in the proximity of another cysteine (C527). This feature suggests that the S-nitrosylated C501 could engage in a disulfide bridge with C527 in TRAP1, resembling the well-known ability of S-nitrosylated cysteines to resolve in disulfide bridge with vicinal cysteines. We used enhanced sampling simulations and in-vitro biochemical assays to address the structural mechanisms induced by TRAP1 S-nitrosylation. We showed that the SNO site induces conformational changes in the proximal cysteine and favors conformations suitable for disulfide bridge formation. We explored 4172 known S-nitrosylated proteins using high-throughput structural analyses. Furthermore, we used a coarse-grained model for 44 protein targets to account for protein flexibility. This resulted in the identification of up to 1248 proximal cysteines, which could sense the redox state of the SNO site, opening new perspectives on the biological effects of redox switches. In addition, we devised two bioinformatic workflows ( https://github.com/ELELAB/SNO_investigation_pipelines ) to identify proximal or vicinal cysteines for a SNO site with accompanying structural annotations. Finally, we analyzed mutations in tumor suppressors or oncogenes in connection with the conformational switch induced by S-nitrosylation. We classified the variants as neutral, stabilizing, or destabilizing for the propensity to be S-nitrosylated and undergo the population-shift mechanism. The methods applied here provide a comprehensive toolkit for future high-throughput studies of new protein candidates, variant classification, and a rich data source for the research community in the NO field.

RosettaDDGPrediction for high-throughput mutational scans: From stability to binding.

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein-protein interaction. Advances in experimental mutational scans allow high-throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease-related variants that can benefit from analyses with structure-based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high-throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high-throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication-ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction.

Cancer-related Mutations with Local or Long-range Effects on an Allosteric Loop of p53.

The tumor protein 53 (p53) is involved in transcription-dependent and independent processes. Several p53 variants related to cancer have been found to impact protein stability. Other variants, on the contrary, might have little impact on structural stability and have local or long-range effects on the p53 interactome. Our group previously identified a loop in the DNA binding domain (DBD) of p53 (residues 207-213) which can recruit different interactors. Experimental structures of p53 in complex with other proteins strengthen the importance of this interface for protein-protein interactions. We here characterized with structure-based approaches somatic and germline variants of p53 which could have a marginal effect in terms of stability and act locally or allosterically on the region 207-213 with consequences on the cytosolic functions of this protein. To this goal, we studied 1132 variants in the p53 DBD with structure-based approaches, accounting also for protein dynamics. We focused on variants predicted with marginal effects on structural stability. We then investigated each of these variants for their impact on DNA binding, dimerization of the p53 DBD, and intramolecular contacts with the 207-213 region. Furthermore, we identified variants that could modulate long-range the conformation of the region 207-213 using a coarse-grain model for allostery and all-atom molecular dynamics simulations. Our predictions have been further validated using enhanced sampling methods for 15 variants. The methodologies used in this study could be more broadly applied to other p53 variants or cases where conformational changes of loop regions are essential in the function of disease-related proteins.

MutateX: an automated pipeline for in silico saturation mutagenesis of protein structures and structural ensembles.

Mutations, which result in amino acid substitutions, influence the stability of proteins and their binding to biomolecules. A molecular understanding of the effects of protein mutations is both of biotechnological and medical relevance. Empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. In silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of known mutations. Often software such as FoldX, while fast and reliable, lack the necessary automation features to apply them in a high-throughput manner. We introduce MutateX, a software to automate the prediction of ΔΔGs associated with the systematic mutation of each residue within a protein, or protein complex to all other possible residue types, using the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles, upon post-translational modifications and in multimeric assemblies. At the heart of MutateX lies an automated pipeline engine that handles input preparation, parallelization and outputs publication-ready figures. We illustrate the MutateX protocol applied to different case studies. The results of the high-throughput scan provided by our tools can help in different applications, such as the analysis of disease-associated mutations, to complement experimental deep mutational scans, or assist the design of variants for industrial applications. MutateX is a collection of Python tools that relies on open-source libraries. It is available free of charge under the GNU General Public License from https://github.com/ELELAB/mutatex.

T cell receptor sequence clustering and antigen specificity.

There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering.

Electromagnetic navigation bronchoscopy for lung nodule evaluation. Patient selection, diagnostic variables and safety.

BACKGROUND: Electromagnetic navigation bronchoscopy (ENB) is a relatively new technique to diagnose pulmonary lesions in patients with reduced lung function. Several parameters have been shown to affect diagnostic yield including patient selection. We performed a prospective registration of data on one hundred patients who consecutively underwent electromagnetic navigation bronchoscopy. Selection criteria, patient characteristics, lesion size, distance to pleura, location of the lesion and presence of bronchus sign on computed tomography were registered. METHODS: Navigation was performed using the superDimension hardware and software system. Patients were referred to ENB from a multidisciplinary team conference. We did not use fluoroscopy, endobronchial ultrasound equipment, rapid onsite evaluation or general anesthesia during the procedure. All patients in whom no malignant diagnose was found were subsequently followed for two years in order to verify a benign nature of the pulmonary lesion. RESULTS: One hundred and nine ENB procedures were performed between September 2009 and November 2014. Overall diagnostic yield was 68%. Twenty seven of 49 malignant tumors were found by ENB leading to a sensitivity for malignancy of 55%. The sensitivity for malignancy was significantly higher for lesions in the upper and middle lobes compared to the lower lobes (P = 0.01). Lesions size, distance to pleura and presence of bronchus sign did not affect sensitivity. CONCLUSION: ENB is a safe diagnostic procedure in an everyday setting with an acceptable diagnostic yield even without addition of supportive diagnostic methods and offers a possibility to diagnose pulmonary nodules in patients for whom other diagnostic procedures are too hazardous or have proven unsuccessful.

New-onset asthma in a bilateral lung transplant patient.

We present a case of new-onset asthma in a 35-year-old man who had undergone bilateral lung transplantation 11 years before due to idiopathic bronchiectasis and pulmonary hypertension. He presented with recurrent episodes of breathlessness, wheezing and coughing. Spirometry demonstrated severe airway obstruction. After treatment with systemic and inhaled corticosteroids and long-acting bronchodilators as well as short-acting beta-agonists as needed, his symptoms resolved and his spirometry normalised. A bronchial mannitol challenge test showed significant airway hyperresponsiveness and is thus consistent for a diagnosis of asthma. To our best knowledge, this is the first case of late new-onset asthma in a lung transplant recipient.

In Vivo Selection of a Unique Tandem Repeat Mediated Azole Resistance Mechanism (TR120) in Aspergillus fumigatus cyp51A, Denmark.

We report a fatal aspergillosis case in which STRAf typing and whole-genome sequencing substantiated in vivo emergence of an azole-resistant Aspergillus fumigatus with a 120-bp tandem repeat in the promoter region of cyp51A. This event, previously restricted to the environment, challenges current understanding of azole resistance development in A. fumigatus.

Effect of intravenous infusion of exenatide (synthetic exendin-4) on glucose-dependent insulin secretion and counterregulation during hypoglycemia.

This study assessed whether glucose-dependent insulin secretion and overall counterregulatory response are preserved during hypoglycemia in the presence of exenatide. Twelve healthy fasted volunteers were randomized in a triple-blind crossover study to receive either intravenous exenatide (0.066 pmol. kg(-1). min(-1)) or placebo during a 270-min stepwise hyperinsulinemic-hypoglycemic clamp (insulin infusion 0.8 mU. kg(-1). min(-1)). Plasma glucose was clamped sequentially at 5.0 (0-120 min), 4.0 (120-180 min), 3.2 (180-240 min), and 2.7 mmol/l (240-270 min). At 270 min, insulin infusion was terminated and plasma glucose increased to approximately 3.2 mmol/l. The time to achieve plasma glucose >/=4 mmol/l thereafter was recorded. Insulin secretory rates (ISRs) and counterregulatory hormones were measured throughout. Glucose profiles were superimposable between the exenatide and placebo arms. In the presence of euglycemic hyperinsulinemia, ISRs in the exenatide arm were approximately 3.5-fold higher than in the placebo arm (353 +/- 29 vs. 100 +/- 29 pmol/min [least-square means +/- SE]). However, ISRs declined similarly and rapidly at all hypoglycemic steps (

One week's treatment with the long-acting glucagon-like peptide 1 derivative liraglutide (NN2211) markedly improves 24-h glycemia and alpha- and beta-cell function and reduces endogenous glucose release in patients with type 2 diabetes.

Glucagon-like peptide 1 (GLP-1) is potentially a very attractive agent for treating type 2 diabetes. We explored the effect of short-term (1 week) treatment with a GLP-1 derivative, liraglutide (NN2211), on 24-h dynamics in glycemia and circulating free fatty acids, islet cell hormone profiles, and gastric emptying during meals using acetaminophen. Furthermore, fasting endogenous glucose release and gluconeogenesis (3-(3)H-glucose infusion and (2)H(2)O ingestion, respectively) were determined, and aspects of pancreatic islet cell function were elucidated on the subsequent day using homeostasis model assessment and first- and second-phase insulin response during a hyperglycemic clamp (plasma glucose approximately 16 mmol/l), and, finally, on top of hyperglycemia, an arginine stimulation test was performed. For accomplishing this, 13 patients with type 2 diabetes were examined in a double-blind, placebo-controlled crossover design. Liraglutide (6 micro g/kg) was administered subcutaneously once daily. Liraglutide significantly reduced the 24-h area under the curve for glucose (P = 0.01) and glucagon (P = 0.04), whereas the area under the curve for circulating free fatty acids was unaltered. Twenty-four-hour insulin secretion rates as assessed by deconvolution of serum C-peptide concentrations were unchanged, indicating a relative increase. Gastric emptying was not influenced at the dose of liraglutide used. Fasting endogenous glucose release was decreased (P = 0.04) as a result of a reduced glycogenolysis (P = 0.01), whereas gluconeogenesis was unaltered. First-phase insulin response and the insulin response to an arginine stimulation test with the presence of hyperglycemia were markedly increased (P < 0.001), whereas the proinsulin/insulin ratio fell (P = 0.001). The disposition index (peak insulin concentration after intravenous bolus of glucose multiplied by insulin sensitivity as assessed by homeostasis model assessment) almost doubled during liraglutide treatment (P < 0.01). Both during hyperglycemia per se and after arginine exposure, the glucagon responses were reduced during liraglutide administration (P < 0.01 and P = 0.01). Thus, 1 week's treatment with a single daily dose of the GLP-1 derivative liraglutide, operating through several different mechanisms including an ameliorated pancreatic islet cell function in individuals with type 2 diabetes, improves glycemic control throughout 24 h of daily living, i.e., prandial and nocturnal periods. This study further emphasizes GLP-1 and its derivatives as a promising novel concept for treatment of type 2 diabetes.

The insulin secretagogues glibenclamide and repaglinide do not influence growth hormone secretion in humans but stimulate glucagon secretion during profound insulin deficiency.

In vitro data have recently suggested that sulfonylureas (SUs) enhance GH secretion by modulating the effects of GHRH and somatostatin in pituitary cells. The present study was undertaken to explore in more detail a possible influence of a single dose of SU (glibenclamide) and a non-SU (repaglinide) insulin secretagogue on circulating GH dynamics. Ten C-peptide-negative type 1 diabetic individuals were examined on three occasions in random order. Either glibenclamide (10.5 mg), repaglinide (8 mg), or placebo was administered after overnight normalization of plasma glucose by iv insulin infusion. Subsequently, GH concentrations were measured regularly after stimulation with GHRH (bolus 0.1 micro g/kg) alone and during concomitant infusion with somatostatin (7 ng.kg(-1).min(-1)). Insulin was replaced at baseline levels (0.25 mU.kg(-1).min(-1)) and plasma glucose clamped at 5-6 mmol/liter. Overall, there were no significant statistical differences in GH responses determined as either GH peak concentrations, integrated levels of GH, or secretory burst mass of GH during the experimental protocol. In contrast, plasma glucagon concentrations were significantly increased during glibenclamide and repaglinide exposure. The present experimental design does not support the hypothesis that acute administration of pharmacological doses of the oral antihyperglycemic agents glibenclamide and repaglinide per se enhance GH release in humans. Additionally, this study shows that these potassium channel inhibitors seem to stimulate glucagon secretion in people who have severe intraislet insulin deficiency (e.g. type 1 diabetes). However, extrapolation of our findings to type 2 diabetic individuals should be done with some caution.