Genetic Characterization of Kidney Failure of Unknown Etiology in Spain: Findings From the GENSEN Study.

RATIONALE & OBJECTIVE: Chronic kidney disease (CKD) of unknown etiology (CKDUE) is one of the main global causes of kidney failure. While genetic studies may identify an etiology in these patients, few studies have implemented genetic testing of CKDUE in population-based series of patients which was the focus of the GENSEN. STUDY DESIGN: Case series. SETTINGS & PARTICIPANTS: 818 patients aged ≤45 years at 51 Spanish centers with CKDUE, and either an estimated GFR <15 mL/min/1.73 m2 or treatment with maintenance dialysis or transplantation. OBSERVATIONS: Genetic testing for 529 genes associated to inherited nephropathies using high-throughput sequencing (HTS). Pathogenic and/or likely pathogenic (P/LP) gene variants concordant with the inheritance pattern were detected in 203 (24.8%) patients. Variants in type IV collagen genes were the most frequent (COL4A5, COL4A4, COL4A3; 35% of total gene variants), followed by NPHP1, PAX2, UMOD, MUC1 and INF2 (7.3%, 5.9%, 2.5%, 2.5% and 2.5% respectively). Overall, 87 novel variants classified as P/LP were identified. The top 5 most common previously undiagnosed diseases were Alport syndrome spectrum (35% of total positive reports), genetic podocytopathies (19%), nephronophthisis (11%), autosomal dominant tubulointerstitial kidney disease (7%) and congenital anomalies of the kidney and urinary tract (CAKUT: 5%). Family history of kidney disease was reported by 191 (23.3 %) participants and by 65/203 (32.0%) patients with P/LP variants. LIMITATIONS: Missing data. Selection bias resulting from voluntary enrollment. CONCLUSIONS: Genomic testing with HTS identified a genetic cause of kidney disease in approximately one quarter of young patients with CKDUE and advanced kidney disease. These findings suggest that genetic studies are a potentially useful tool for the evaluation of people with CKDUE.

A novel mortality risk score for emphysematous pyelonephritis: A multicenter study of the Global Research in the Emphysematous Pyelonephritis group.

Background: Emphysematous pyelonephritis (EPN) is a necrotizing infection of the kidney and the surrounding tissues associated with considerable mortality. We aimed to formulate a score that classifies the risk of mortality in patients with EPN at hospital admission. Materials and methods: Patients diagnosed with EPN between 2013 and 2020 were retrospectively included. Data from 15 centers (70%) were used to develop the scoring system, and data from 7 centers (30%) were used to validate it. Univariable and multivariable logistic regression analyses were performed to identify independent factors related to mortality. Receiver operating characteristic curve analysis was performed to construct the scoring system and calculate the risk of mortality. A standardized regression coefficient was used to quantify the discriminating power of each factor to convert the individual coefficients into points. The area under the curve was used to quantify the scoring system performance. An 8-point scoring system for the mortality risk was created (range, 0-7). Results: In total, 570 patients were included (400 in the test group and 170 in the validation group). Independent predictors of mortality in the multivariable logistic regression were included in the scoring system: quick Sepsis-related Organ Failure Assessment score ≥2 (2 points), anemia, paranephric gas extension, leukocyte count >22,000/µL, thrombocytopenia, and hyperglycemia (1 point each). The mortality rate was <5% for scores ≤3, 83.3% for scores 6, and 100% for scores 7. The area under the curve was 0.90 (95% confidence interval, 0.84-0.95) for test and 0.91 (95% confidence interval, 0.84-0.97) for the validation group. Conclusions: Our score predicts the risk of mortality in patients with EPN at presentation and may help clinicians identify patients at a higher risk of death.

Pivotal role of BCL11B in the immune, hematopoietic and nervous systems: a review of the BCL11B-associated phenotypes from the genetic perspective.

The transcription factor BCL11B plays an essential role in the development of central nervous system and T cell differentiation by regulating the expression of numerous genes involved in several pathways. Monoallelic defects in the BCL11B gene leading to loss-of-function are associated with a wide spectrum of phenotypes, including neurological disorders with or without immunological features and susceptibility to hematological malignancies. From the genetic point of view, the landscape of BCL11B mutations reported so far does not fully explain the genotype-phenotype correlation. In this review, we sought to compile the phenotypic and genotypic variables associated with previously reported mutations in this gene in order to provide a better understanding of the consequences of deleterious variants. We also highlight the importance of a careful evaluation of the mutation type, its location and the pattern of inheritance of the variants in order to assign the most accurate pathogenicity and actionability of the genetic findings.

Physico-chemical characterization of the tumour microenvironment of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive lethal malignancy that accounts for more than 90% of pancreatic cancer diagnoses. Our research is focused on the physico-chemical properties of the tumour microenvironment (TME), including its tumoural extracellular matrix (tECM), as they may have an important impact on the success of cancer therapies. PDAC xenografts and their decellularized tECM offer a great material source for research in terms of biomimicry with the original human tumour. Our aim was to evaluate and quantify the physico-chemical properties of the PDAC TME. Both cellularized (native TME) and decellularized (tECM) patient-derived PDAC xenografts were analyzed. A factorial design of experiments identified an optimal combination of factors for effective xenograft decellularization. Our results provide a complete advance in our understanding of the PDAC TME and its corresponding stroma, showing that it presents an interconnected porous architecture with very low permeability and small pores due to the contractility of the cellular components. This fact provides a potential therapeutic strategy based on the therapeutic agent size.

Novel frameshift variants expand the map of the genetic defects in IRF2BP2.

Background: At present, the knowledge about disease-causing mutations in IRF2BP2 is very limited because only a few patients affected by this condition have been reported. As previous studies have described, the haploinsufficiency of this interferon transcriptional corepressors leads to the development of CVID. Very recently, a more accurate phenotype produced by truncating variants in this gene has been defined, manifesting CVID with gastrointestinal inflammatory symptoms and autoimmune manifestations. Methods: We analyzed 5 index cases with suspected primary immunodeficiency by high throughput sequencing. They were submitted for a genetic test with a panel of genes associated with immune system diseases, including IRF2BP2. The screening of SNVs, indels and CNVs fulfilling the criteria with very low allelic frequency and high protein impact, revealed five novel variants in IRF2BP2. In addition, we isolated both wild-type and mutated allele of the cDNA from one of the families. Results: In this study, we report five novel loss-of-function (LoF) mutations in IRF2BP2 that likely cause primary immunodeficiency, with CVID as more frequent phenotype, variable expression of inflammatory gastrointestinal features, and one patient with predisposition of viral infection. All identified variants were frameshift changes, and one of them was a large deletion located on chromosome 1q42, which includes the whole sequence of IRF2BP2, among other genes. Both de novo and dominant modes of inheritance were observed in the families here presented, as well as incomplete penetrance. Conclusions: We describe novel variants in a delimited low-complex region, which may be considered a hotspot in IRF2BP2. Moreover, this is the first time that a large CNV in IRF2BP2 has been reported to cause CVID. The distinct mechanisms than LoF in IRF2BP2 could cause different phenotype compared with the mainly described. Further investigations are necessary to comprehend the regulatory mechanisms of IRF2BP2, which could be under variable expression of the disease.

Fluid flow to mimic organ function in 3D in vitro models.

Many different strategies can be found in the literature to model organ physiology, tissue functionality, and disease in vitro; however, most of these models lack the physiological fluid dynamics present in vivo. Here, we highlight the importance of fluid flow for tissue homeostasis, specifically in vessels, other lumen structures, and interstitium, to point out the need of perfusion in current 3D in vitro models. Importantly, the advantages and limitations of the different current experimental fluid-flow setups are discussed. Finally, we shed light on current challenges and future focus of fluid flow models applied to the newest bioengineering state-of-the-art platforms, such as organoids and organ-on-a-chip, as the most sophisticated and physiological preclinical platforms.

A hybrid physics-based and data-driven framework for cellular biological systems: Application to the morphogenesis of organoids.

How cells orchestrate their cellular functions remains a crucial question to unravel how they organize in different patterns. We present a framework based on artificial intelligence to advance the understanding of how cell functions are coordinated spatially and temporally in biological systems. It consists of a hybrid physics-based model that integrates both mechanical interactions and cell functions with a data-driven model that regulates the cellular decision-making process through a deep learning algorithm trained on image data metrics. To illustrate our approach, we used data from 3D cultures of murine pancreatic ductal adenocarcinoma cells (PDAC) grown in Matrigel as tumor organoids. Our approach allowed us to find the underlying principles through which cells activate different cell processes to self-organize in different patterns according to the specific microenvironmental conditions. The framework proposed here expands the tools for simulating biological systems at the cellular level, providing a novel perspective to unravel morphogenetic patterns.

Effects of tumour heterogeneous properties on modelling the transport of radiative particles.

Dose calculation plays a critical role in radiotherapy (RT) treatment planning, and there is a growing need to develop accurate dose deposition models that incorporate heterogeneous tumour properties. Deterministic models have demonstrated their capability in this regard, making them the focus of recent treatment planning studies as they serve as a basis for simplified models in RT treatment planning. In this study, we present a simplified deterministic model for photon transport based on the Boltzmann transport equation (BTE) as a proof-of-concept to illustrate the impact of heterogeneous tumour properties on RT treatment planning. We employ the finite element method (FEM) to simulate the photon flux and dose deposition in real cases of diffuse intrinsic pontine glioma (DIPG) and neuroblastoma (NB) tumours. Importantly, in light of the availability of pipelines capable of extracting tumour properties from magnetic resonance imaging (MRI) data, we highlight the significance of such data. Specifically, we utilise cellularity data extracted from DIPG and NB MRI images to demonstrate the importance of heterogeneity in dose calculation. Our model simplifies the process of simulating a RT treatment system and can serve as a useful starting point for further research. To simulate a full RT treatment system, one would need a comprehensive model that couples the transport of electrons and photons.

Hydrocolloids of Egg White and Gelatin as a Platform for Hydrogel-Based Tissue Engineering.

Innovative materials are needed to produce scaffolds for various tissue engineering and regenerative medicine (TERM) applications, including tissue models. Materials derived from natural sources that offer low production costs, easy availability, and high bioactivity are highly preferred. Chicken egg white (EW) is an overlooked protein-based material. Whilst its combination with the biopolymer gelatin has been investigated in the food technology industry, mixed hydrocolloids of EW and gelatin have not been reported in TERM. This paper investigates these hydrocolloids as a suitable platform for hydrogel-based tissue engineering, including 2D coating films, miniaturized 3D hydrogels in microfluidic devices, and 3D hydrogel scaffolds. Rheological assessment of the hydrocolloid solutions suggested that temperature and EW concentration can be used to fine-tune the viscosity of the ensuing gels. Fabricated thin 2D hydrocolloid films presented globular nano-topography and in vitro cell work showed that the mixed hydrocolloids had increased cell growth compared with EW films. Results showed that hydrocolloids of EW and gelatin can be used for creating a 3D hydrogel environment for cell studies inside microfluidic devices. Finally, 3D hydrogel scaffolds were fabricated by sequential temperature-dependent gelation followed by chemical cross-linking of the polymeric network of the hydrogel for added mechanical strength and stability. These 3D hydrogel scaffolds displayed pores, lamellae, globular nano-topography, tunable mechanical properties, high affinity for water, and cell proliferation and penetration properties. In conclusion, the large range of properties and characteristics of these materials provide a strong potential for a large variety of TERM applications, including cancer models, organoid growth, compatibility with bioprinting, or implantable devices.

Collagen-Laponite Nanoclay Hydrogels for Tumor Spheroid Growth.

The extracellular matrix (ECM) plays an important regulatory role in the development and progression of tumoral tissue. Its functions and properties are crucial in determining tumor cell behavior such as invasion, migration, and malignancy development. Our study explores the role of collagen type I in cancer development and spread using engineered tumor models like multicellular spheroids grown in collagen-based hydrogels to simulate early tumor formation. We employ microfluidic techniques to test the hypothesis that (i) adding Laponite nanoclay to collagen hydrogels modifies mechanical and rheological properties and (ii) changing the stiffness of the collagen microenvironment affects tumor spheroid growth. Our findings support our theories and suggest the use of ECM components and engineered tumor models in cancer research, offering a biocompatible and biomimetic method to tailor the mechanical properties of conventional collagen hydrogels.

Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment.

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

PhysiCOOL: A generalized framework for model Calibration and Optimization Of modeLing projects.

In silico models of biological systems are usually very complex and rely on a large number of parameters describing physical and biological properties that require validation. As such, parameter space exploration is an essential component of computational model development to fully characterize and validate simulation results. Experimental data may also be used to constrain parameter space (or enable model calibration) to enhance the biological relevance of model parameters. One widely used computational platform in the mathematical biology community is PhysiCell, which provides a standardized approach to agent-based models of biological phenomena at different time and spatial scales. Nonetheless, one limitation of PhysiCell is the lack of a generalized approach for parameter space exploration and calibration that can be run without high-performance computing access. Here, we present PhysiCOOL, an open-source Python library tailored to create standardized calibration and optimization routines for PhysiCell models.

Hybrid computational models of multicellular tumour growth considering glucose metabolism.

Cancer cells metabolize glucose through metabolic pathways that differ from those used by healthy and differentiated cells. In particular, tumours have been shown to consume more glucose than their healthy counterparts and to use anaerobic metabolic pathways, even under aerobic conditions. Nevertheless, scientists have still not been able to explain why cancer cells evolved to present an altered metabolism and what evolutionary advantage this might provide them. Experimental and computational models have been increasingly used in recent years to understand some of these biological questions. Multicellular tumour spheroids are effective experimental models as they replicate the initial stages of avascular solid tumour growth. Furthermore, these experiments generate data which can be used to calibrate and validate computational studies that aim to simulate tumour growth. Hybrid models are of particular relevance in this field of research because they model cells as individual agents while also incorporating continuum representations of the substances present in the surrounding microenvironment that may participate in intracellular metabolic networks as concentration or density distributions. Henceforth, in this review, we explore the potential of computational modelling to reveal the role of metabolic reprogramming in tumour growth.

Computational modelling of the mechanical behaviour of protein-based hydrogels.

Protein-based hydrogels have been extensively studied in the field of biomaterials given their ability to mimic living tissues and their special resemblance to the extracellular matrix. Despite this, the methods used for the control of mechanical properties of hydrogels are very limited, focusing mainly on their elasticity, with an often unrealistic characterization of mechanical properties such as extensibility, stiffness and viscoelasticity. Being able to control these properties is essential for the development of new biomaterials, since it has been demonstrated that mechanical properties affect cell behaviour and biological processes. To better understand the mechanical behaviour of these biopolymers, a computational model is here developed to characterize the mechanical behaviour of two different protein-based hydrogels. Strain-stress tests and stress-relaxation tests are evaluated computationally and compared to the results obtained experimentally in a previous work. To achieve this goal the Finite Element Method is used, combining hyperelastic and viscoelastic models. Different hyperelastic constitutive models (Mooney-Rivlin, Neo-Hookean, first and third order Ogden, and Yeoh) are proposed to estimate the mechanical properties of the protein-based hydrogels by least-square fitting of the in-vitro uniaxial test results. Among these models, the first order Ogden model with a viscoelastic model defined in Prony parameters better reproduces the strain-stress response and the change of stiffness with strain observed in the in-vitro tests.

Characterization of mutant versions of the R-RAS2/TC21 GTPase found in tumors.

The R-RAS2 GTP hydrolase (GTPase) (also known as TC21) has been traditionally considered quite similar to classical RAS proteins at the regulatory and signaling levels. Recently, a long-tail hotspot mutation targeting the R-RAS2/TC21 Gln72 residue (Q72L) was identified as a potent oncogenic driver. Additional point mutations were also found in other tumors at low frequencies. Despite this, little information is available regarding the transforming role of these mutant versions and their relevance for the tumorigenic properties of already-transformed cancer cells. Here, we report that many of the RRAS2 mutations found in human cancers are highly transforming when expressed in immortalized cell lines. Moreover, the expression of endogenous R-RAS2Q72L is important for maintaining optimal levels of PI3K and ERK activities as well as for the adhesion, invasiveness, proliferation, and mitochondrial respiration of ovarian and breast cancer cell lines. Endogenous R-RAS2Q72L also regulates gene expression programs linked to both cell adhesion and inflammatory/immune-related responses. Endogenous R-RAS2Q72L is also quite relevant for the in vivo tumorigenic activity of these cells. This dependency is observed even though these cancer cell lines bear concurrent gain-of-function mutations in genes encoding RAS signaling elements. Finally, we show that endogenous R-RAS2, unlike the case of classical RAS proteins, specifically localizes in focal adhesions. Collectively, these results indicate that gain-of-function mutations of R-RAS2/TC21 play roles in tumor initiation and maintenance that are not fully redundant with those regulated by classical RAS oncoproteins.

3D collagen migration patterns reveal a SMAD3-dependent and TGF-ß1-independent mechanism of recruitment for tumour-associated fibroblasts in lung adenocarcinoma.

BACKGROUND: The TGF-ß1 transcription factor SMAD3 is epigenetically repressed in tumour-associated fibroblasts (TAFs) from lung squamous cell carcinoma (SCC) but not adenocarcinoma (ADC) patients, which elicits a compensatory increase in SMAD2 that renders SCC-TAFs less fibrotic. Here we examined the effects of altered SMAD2/3 in fibroblast migration and its impact on the desmoplastic stroma formation in lung cancer. METHODS: We used a microfluidic device to examine descriptors of early protrusions and subsequent migration in 3D collagen gels upon knocking down SMAD2 or SMAD3 by shRNA in control fibroblasts and TAFs. RESULTS: High SMAD3 conditions as in shSMAD2 fibroblasts and ADC-TAFs exhibited a migratory advantage in terms of protrusions (fewer and longer) and migration (faster and more directional) selectively without TGF-ß1 along with Erk1/2 hyperactivation. This enhanced migration was abrogated by TGF-ß1 as well as low glucose medium and the MEK inhibitor Trametinib. In contrast, high SMAD2 fibroblasts were poorly responsive to TGF-ß1, high glucose and Trametinib, exhibiting impaired migration in all conditions. CONCLUSIONS: The basal migration advantage of high SMAD3 fibroblasts provides a straightforward mechanism underlying the larger accumulation of TAFs previously reported in ADC compared to SCC. Moreover, our results encourage using MEK inhibitors in ADC-TAFs but not SCC-TAFs.

Incidence, Management Experience and Characteristics of Patients with Giardiasis and Common Variable Immunodeficiency.

Common variable immunodeficiency (CVID) is an antibody immunodeficiency with a wide variety of clinical and immunological manifestations, and whose genetic cause is found in about 25% of diagnosed cases. Giardia lamblia is one of the main causes of gastrointestinal infections in CVID. 5-Nitroimidazoles are the most used first-line treatment, but nitroimidazole-refractory giardiasis is increasing. Nevertheless, only a few cases of refractory giardiasis in CVID have been reported. This study aimed to determine the incidence of Giardia infection in our CVID cohort, shows our management experience and describes patients' phenotypic features. Clinical data collection, immunological, immunogenetics and microbiology assays were performed, and previous cases of giardiasis in CVID were reviewed. The incidence of symptomatic giardiasis was 12.9%. The main immunological features were undetectable or decreased IgA levels and reduced switched memory B cells. A probable PTEN pathogenic variant was detected in one. Three patients responded to metronidazole but suffered reinfections, and one was a refractory giardiasis eradicated with innovative quinacrine plus paromomycin combination. This work could contribute to the decision-making and therapeutic management of future patients with CVID and giardiasis, highlighting the importance of the early detection and treatment of infections in patients with CVID to ensure a good quality of life.

Prognosis of Extended-Spectrum-Beta-Lactamase-Producing Agents in Emphysematous Pyelonephritis-Results from a Large, Multicenter Series.

BACKGROUND: Emphysematous pyelonephritis (EPN) is a necrotizing infection of the kidney and surrounding tissues with significant mortality. We aimed to assess the clinical factors and their influence on prognosis in patients being managed for EPN with and without ESBL-producing bacteria and to identify if those with EPN due to ESBL infections fared any different. METHODS: A retrospective analysis was performed on patients with EPN diagnosis from 22 centers across 11 countries (between 2013 and 2020). Demographics, clinical presentation, biochemical parameters, radiological features, microbiological characteristics, and therapeutic management were assessed. Univariable and multivariable analyses were performed to determine the independent variables associated with ESBL pathogens. A comparison of ESBL and non-ESBL mortality was performed evaluating treatment modality. RESULTS: A total of 570 patients were included. Median (IQR) age was 57 (47-65) years. Among urine cultures, the most common isolated pathogen was Escherichia coli (62.2%). ESBL-producing agents were present in 291/556 urine cultures (52.3%). In multivariable analysis, thrombocytopenia (OR 1.616 95% CI 1.081-2.413, p = 0.019), and Huang-Tseng type 4 (OR 1.948 95% CI 1.005-3.778, p= 0.048) were independent predictors of ESBL pathogens. Patients with Huang-Tseng Scale type 1 had 55% less chance of having ESBL-producing pathogens (OR 1.616 95% CI 1.081-2.413, p = 0.019). Early nephrectomy (OR 2.3, p = 0.029) and delayed nephrectomy (OR 2.4, p = 0.015) were associated with increased mortality in patients with ESBL infections. Conservative/minimally invasive management reported an inverse association with mortality (OR 0.314, p = 0.001). CONCLUSIONS: ESBL bacteria in EPN were not significantly associated with mortality in EPN. However, ESBL infections were associated with poor prognosis when patients underwent nephrectomy compared conservative/minimally invasive management.

Feedback between mechanosensitive signaling and active forces governs endothelial junction integrity.

The formation and recovery of gaps in the vascular endothelium governs a wide range of physiological and pathological phenomena, from angiogenesis to tumor cell extravasation. However, the interplay between the mechanical and signaling processes that drive dynamic behavior in vascular endothelial cells is not well understood. In this study, we propose a chemo-mechanical model to investigate the regulation of endothelial junctions as dependent on the feedback between actomyosin contractility, VE-cadherin bond turnover, and actin polymerization, which mediate the forces exerted on the cell-cell interface. Simulations reveal that active cell tension can stabilize cadherin bonds, but excessive RhoA signaling can drive bond dissociation and junction failure. While actin polymerization aids gap closure, high levels of Rac1 can induce junction weakening. Combining the modeling framework with experiments, our model predicts the influence of pharmacological treatments on the junction state and identifies that a critical balance between RhoA and Rac1 expression is required to maintain junction stability. Our proposed framework can help guide the development of therapeutics that target the Rho family of GTPases and downstream active mechanical processes.

A 3D multi-agent-based model for lumen morphogenesis: the role of the biophysical properties of the extracellular matrix.

The correct function of many organs depends on proper lumen morphogenesis, which requires the orchestration of both biological and mechanical aspects. However, how these factors coordinate is not yet fully understood. Here, we focus on the development of a mechanistic model for computationally simulating lumen morphogenesis. In particular, we consider the hydrostatic pressure generated by the cells' fluid secretion as the driving force and the density of the extracellular matrix as regulators of the process. For this purpose, we develop a 3D agent-based-model for lumen morphogenesis that includes cells' fluid secretion and the density of the extracellular matrix. Moreover, this computer-based model considers the variation in the biological behavior of cells in response to the mechanical forces that they sense. Then, we study the formation of the lumen under different-mechanical scenarios and conclude that an increase in the matrix density reduces the lumen volume and hinders lumen morphogenesis. Finally, we show that the model successfully predicts normal lumen morphogenesis when the matrix density is physiological and aberrant multilumen formation when the matrix density is excessive. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-022-01654-1.