Novel enzymes for biodegradation of polycyclic aromatic hydrocarbons identified by metagenomics and functional analysis in short-term soil microcosm experiments.

Polycyclic aromatic hydrocarbons (PAHs) are highly toxic, carcinogenic substances. On soils contaminated with PAHs, crop cultivation, animal husbandry and even the survival of microflora in the soil are greatly perturbed, depending on the degree of contamination. Most microorganisms cannot tolerate PAH-contaminated soils, however, some microbial strains can adapt to these harsh conditions and survive on contaminated soils. Analysis of the metagenomes of contaminated environmental samples may lead to discovery of PAH-degrading enzymes suitable for green biotechnology methodologies ranging from biocatalysis to pollution control. In the present study, our goal was to apply a metagenomic data search to identify efficient novel enzymes in remediation of PAH-contaminated soils. The metagenomic hits were further analyzed using a set of bioinformatics tools to select protein sequences predicted to encode well-folded soluble enzymes. Three novel enzymes (two dioxygenases and one peroxidase) were cloned and used in soil remediation microcosms experiments. The experimental design of the present study aimed at evaluating the effectiveness of the novel enzymes on short-term PAH degradation in the soil microcosmos model. The novel enzymes were found to be efficient for degradation of naphthalene and phenanthrene. Adding the inorganic oxidant CaO2 further increased the degrading potential of the novel enzymes for anthracene and pyrene. We conclude that metagenome mining paired with bioinformatic predictions, structural modelling and functional assays constitutes a powerful approach towards novel enzymes for soil remediation.

Cost-effectiveness of genetic testing of endocrine tumor patients using a comprehensive hereditary cancer gene panel.

INTRODUCTION: Heterogenous clinical manifestations, overlapping phenotypes and complex genetic backgrounds are common in patients with endocrine tumors. There are no comprehensive recommendations for genetic testing and counselling of these patients compared to other hereditary cancer syndromes. The application of multigene panel testing is common in clinical genetic laboratories, but their performance for patients with endocrine tumors has not been assessed. METHODS: As a national reference center, we prospectively tested the diagnostic utility and cost-efficiency of a multigene panel covering 113 genes representing genetic susceptibility for solid tumors. 1279 patients (including 96 cases with endocrine tumors) were evaluated between October 2021 and December 2022 who were suspected to have hereditary tumor syndromes. RESULTS: The analytical performance of the hereditary cancer panel was suitable for diagnostic testing. Clinical diagnosis was confirmed in 24% (23/96); incidental findings in genes not associated with the patient's phenotype were identified in 5% (5/96). A further 7% of pathogenic/likely pathogenic variants were detected in genes with potential genetic susceptibility roles but currently no clear clinical consequence. Cost-benefit analysis showed that the application of a more comprehensive gene panel in a diagnostic laboratory yielded a shorter turnaround time and provided additional genetic results with the same cost and workload. DISCUSSION: Using comprehensive multigene panel results in faster turnaround time and cost-efficiently identifies genetic alterations in hereditary endocrine tumor syndromes. Incidentally identified variants in patients with poor prognoses may serve as a potential therapeutic target in tumors where therapeutic possibilities are limited.

Gluing GAP to RAS Mutants: A New Approach to an Old Problem in Cancer Drug Development.

Mutated genes may lead to cancer development in numerous tissues. While more than 600 cancer-causing genes are known today, some of the most widespread mutations are connected to the RAS gene; RAS mutations are found in approximately 25% of all human tumors. Specifically, KRAS mutations are involved in the three most lethal cancers in the U.S., namely pancreatic ductal adenocarcinoma, colorectal adenocarcinoma, and lung adenocarcinoma. These cancers are among the most difficult to treat, and they are frequently excluded from chemotherapeutic attacks as hopeless cases. The mutated KRAS proteins have specific three-dimensional conformations, which perturb functional interaction with the GAP protein on the GAP-RAS complex surface, leading to a signaling cascade and uncontrolled cell growth. Here, we describe a gluing docking method for finding small molecules that bind to both the GAP and the mutated KRAS molecules. These small molecules glue together the GAP and the mutated KRAS molecules and may serve as new cancer drugs for the most lethal, most difficult-to-treat, carcinomas. As a proof of concept, we identify two new, drug-like small molecules with the new method; these compounds specifically inhibit the growth of the PANC-1 cell line with KRAS mutation G12D in vitro and in vivo. Importantly, the two new compounds show significantly lower IC50 and higher specificity against the G12D KRAS mutant human pancreatic cancer cell line PANC-1, as compared to the recently described selective G12D KRAS inhibitor MRTX-1133.

Discovery and biocatalytic characterization of opine dehydrogenases by metagenome mining.

Enzymatic processes play an increasing role in synthetic organic chemistry which requires the access to a broad and diverse set of enzymes. Metagenome mining is a valuable and efficient way to discover novel enzymes with unique properties for biotechnological applications. Here, we report the discovery and biocatalytic characterization of six novel metagenomic opine dehydrogenases from a hot spring environment (mODHs) (EC 1.5.1.X). These enzymes catalyze the asymmetric reductive amination between an amino acid and a keto acid resulting in opines which have defined biochemical roles and represent promising building blocks for pharmaceutical applications. The newly identified enzymes exhibit unique substrate specificity and higher thermostability compared to known examples. The feature that they preferably utilize negatively charged polar amino acids is so far unprecedented for opine dehydrogenases. We have identified two spatially correlated positions in their active sites that govern this substrate specificity and demonstrated a switch of substrate preference by site-directed mutagenesis. While they still suffer from a relatively narrow substrate scope, their enhanced thermostability and the orthogonality of their substrate preference make them a valuable addition to the toolbox of enzymes for reductive aminations. Importantly, enzymatic reductive aminations with highly polar amines are very rare in the literature. Thus, the preparative-scale enzymatic production, purification, and characterization of three highly functionalized chiral secondary amines lend a special significance to our work in filling this gap. KEY POINTS: • Six new opine dehydrogenases have been discovered from a hot spring metagenome • The newly identified enzymes display a unique substrate scope • Substrate specificity is governed by two correlated active-site residues.

Robust circuitry-based scores of structural importance of human brain areas.

We consider the 1015-vertex human consensus connectome computed from the diffusion MRI data of 1064 subjects. We define seven different orders on these 1015 graph vertices, where the orders depend on parameters derived from the brain circuitry, that is, from the properties of the edges (or connections) incident to the vertices ordered. We order the vertices according to their degree, the sum, the maximum, and the average of the fiber counts on the incident edges, and the sum, the maximum and the average length of the fibers in the incident edges. We analyze the similarities of these seven orders by the Spearman correlation coefficient and by their inversion numbers and have found that all of these seven orders have great similarities. In other words, if we interpret the orders as scoring of the importance of the vertices in the consensus connectome, then the scores of the vertices will be similar in all seven orderings. That is, important vertices of the human connectome typically have many neighbors connected with long and thick axonal fibers (where thickness is measured by fiber numbers), and their incident edges have high maximum and average values of length and fiber-number parameters, too. Therefore, these parameters may yield robust ways of deciding which vertices are more important in the anatomy of our brain circuitry than the others.

PALB2 Variants Extend the Mutational Profile of Hungarian Patients with Breast and Ovarian Cancer.

BACKGROUND: The pathogenic/likely pathogenic (P/LP) variant detection rate and profile of PALB2, the third most important breast cancer gene, may vary between different populations. METHODS: PALB2 was analyzed in peripheral blood samples of three independent cohorts: prospectively between September 2021 and March 2023 (i) in 1280 consecutive patients with breast and/or ovarian cancer (HBOC), (ii) in 568 patients with other cancers (controls), and retrospectively, (iii) in 191 young breast cancer (<33 years, yBC) patients. These data were compared with data of 134,187 non-cancer individuals retrieved from the Genome Aggregation Database. RESULTS: Altogether, 235 cases (235/1280; 18.3%) carried at least one P/LP variant in one of the HBOC susceptibility genes. P/LP PALB2 variants were identified in 18 patients (1.4%; 18/1280) in the HBOC and 3 cases (1.5%; 3/191) in the yBC group. In the control group, only one patient had a disease-causing PALB2 variant (0.17%; 1/568) as a secondary finding not related to the disease, which was similar (0.15%; 205/134,187) in the non-cancer control group. The NM_024675.4:c.509_510delGA variant was the most common among our patients (33%; 6/18). We did not find a significant difference in the incidence of PALB2 disease-causing variants according to age; however, the median age of tumor onset was lower in PALB2 P/LP carriers versus wild-type patients (44 vs. 48 years). In our cohort, the odds ratio for breast cancer risk in women with PALB2 P/LP variants was between 8.1 and 9.3 compared to non-HBOC cancer patients and the non-cancer population, respectively. CONCLUSIONS: PALB2 P/LP variants are not uncommon among breast and/or ovarian cancer patients. Their incidence was the same in the two breast cancer cohorts studied but may occur rarely in patients with non-breast/ovarian cancer. The c.509_510delGA variant is particularly common in the studied Hungarian patient population.

ONC201/TIC10 enhances durability of mTOR inhibitor everolimus in metastatic ER+ breast cancer.

The mTOR inhibitor, everolimus, is an important clinical management component of metastatic ER+ breast cancer (BC). However, most patients develop resistance and progress on therapy, highlighting the need to discover strategies that increase mTOR inhibitor effectiveness. We developed ER+ BC cell lines, sensitive or resistant to everolimus, and discovered that combination treatment of ONC201/TIC10 with everolimus inhibited cell growth in 2D/3D in vitro studies. We confirmed increased therapeutic response in primary patient cells progressing on everolimus, supporting clinical relevance. We show that ONC201/TIC10 mechanism in metastatic ER+ BC cells involves oxidative phosphorylation inhibition and stress response activation. Transcriptomic analysis in everolimus resistant breast patient tumors and mitochondrial functional assays in resistant cell lines demonstrated increased mitochondrial respiration dependency, contributing to ONC201/TIC10 sensitivity. We propose that ONC201/TIC10 and modulation of mitochondrial function may provide an effective add-on therapy strategy for patients with metastatic ER+ BCs resistant to mTOR inhibitors.

Breast cancer is one of the most frequently diagnosed cancers globally, particularly among women. The most common type of breast cancer expresses a receptor for the hormone estrogen. Many treatments block the activity of estrogen and therefore slow or block the development and spread of this type of breast cancer. For patients with advanced breast cancer, hormone-blocking treatments work best in combination with other drugs, including one called everolimus. However, in many patients the cancer cells become resistant to these therapies, leading to disease progression and decreased survival. To explore treatment strategies that could enhance the effectiveness of existing therapies for breast cancer, Farmaki et al. studied how cancer cells which had become resistant to everolimus responded when treated with an experimental drug called ONC201/TIC10. A combination of everolimus and ONC201/TIC10 inhibited growth of resistant cancer cells that had been grown in a three-dimensional arrangement to mimic human tumors. Moreover, the drug combination effectively targeted breast cancer cells collected from patients whose cancer had progressed while being treated with everolimus, suggesting that ONC201/TIC10 could be relevant in a clinical setting. Finally, molecular and biochemical experiments revealed that the drug ONC201/TIC10 works by disrupting the pathways that everolimus-resistant cancer cells use to generate the energy required to grow and proliferate. Taken together these findings suggest that ONC201/TIC10 may provide an effective add-on therapy for patients with certain types of advanced breast cancer that are no longer responding to everolimus. Before this becomes a reality for patients, however, there will have to be more experimental testing of ONC201/TIC10 to determine optimal dosing and timing strategy for future clinical trials.

Challenging interpretation of germline TP53 variants based on the experience of a national comprehensive cancer centre.

TP53 variant interpretation is still challenging, especially in patients with attenuated Li-Fraumeni syndrome (LFS). We investigated the prevalence of pathogenic/likely pathogenic (P/LP) variants and LFS disease in the Hungarian population of cancer patients. By testing 893 patients with multiplex or familial cancer, we identified and functionally characterized novel splice variants of TP53 helping accurate variant classification. The differences among various semi-automated interpretation platforms without manual curation highlight the importance of focused interpretation as the automatic classification systems do not apply the TP53-specific criteria. The predicted frequency of the TP53 P/LP variants in Hungary is 0.3 per million which most likely underestimates the real prevalence. The higher detection rate of disease-causing variants in patients with attenuated LFS phenotype compared to the control population (OR 12.5; p < 0.0001) may raise the potential benefit of the TP53 genetic testing as part of the hereditary cancer panels of patients with multiple or familial cancer even when they do not meet Chompret criteria. Tumours developed at an earlier age in phenotypic LFS patients compared to the attenuated LFS patients which complicates genetic counselling as currently there are no different recommendations in surveillance protocols for LFS, phenotypic LFS, and attenuated LFS patients.

Cell facilitation promotes growth and survival under drug pressure in breast cancer.

The interplay of positive and negative interactions between drug-sensitive and resistant cells influences the effectiveness of treatment in heterogeneous cancer cell populations. Here, we study interactions between estrogen receptor-positive breast cancer cell lineages that are sensitive and resistant to ribociclib-induced cyclin-dependent kinase 4 and 6 (CDK4/6) inhibition. In mono- and coculture, we find that sensitive cells grow and compete more effectively in the absence of treatment. During treatment with ribociclib, sensitive cells survive and proliferate better when grown together with resistant cells than when grown in monoculture, termed facilitation in ecology. Molecular, protein, and genomic analyses show that resistant cells increase metabolism and production of estradiol, a highly active estrogen metabolite, and increase estrogen signaling in sensitive cells to promote facilitation in coculture. Adding estradiol in monoculture provides sensitive cells with increased resistance to therapy and cancels facilitation in coculture. Under partial inhibition of estrogen signaling through low-dose endocrine therapy, estradiol supplied by resistant cells facilitates sensitive cell growth. However, a more complete blockade of estrogen signaling, through higher-dose endocrine therapy, diminished the facilitative growth of sensitive cells. Mathematical modeling quantifies the strength of competition and facilitation during CDK4/6 inhibition and predicts that blocking facilitation has the potential to control both resistant and sensitive cancer cell populations and inhibit the emergence of a refractory population during cell cycle therapy.

A common genetic variation in GZMB may associate with cancer risk in patients with Lynch syndrome.

Lynch syndrome (LS), also known as hereditary nonpolyposis colorectal cancer syndrome (HNPCC) is a common genetic predisposition to cancer due to germline mutations in genes affecting DNA mismatch repair. Due to mismatch repair deficiency, developing tumors are characterized by microsatellite instability (MSI-H), high frequency of expressed neoantigens and good clinical response to immune checkpoint inhibitors. Granzyme B (GrB) is the most abundant serine protease in the granules of cytotoxic T-cells and natural killer cells, mediating anti-tumor immunity. However, recent results confirm a diverse range of physiological functions of GrB including that in extracellular matrix remodelling, inflammation and fibrosis. In the present study, our aim was to investigate whether a frequent genetic variation of GZMB, the gene encoding GrB, constituted by three missense single nucleotide polymorphisms (rs2236338, rs11539752 and rs8192917) has any association with cancer risk in individuals with LS. In silico analysis and genotype calls from whole exome sequencing data in the Hungarian population confirmed that these SNPs are closely linked. Genotyping results of rs8192917 on a cohort of 145 individuals with LS demonstrated an association of the CC genotype with lower cancer risk. In silico prediction proposed likely GrB cleavage sites in a high proportion of shared neontigens in MSI-H tumors. Our results propose the CC genotype of rs8192917 as a potential disease-modifying genetic factor in LS.

Genome sequencing-based discovery of a novel deep intronic APC pathogenic variant causing exonization.

Familial adenomatous polyposis (FAP) is a hereditary cancer syndrome that occurs as a result of germline mutations in the APC gene. Despite a clear clinical diagnosis of FAP, a certain proportion of the APC variants are not readily detectable through conventional genotyping routines. We accomplished genome sequencing in duo of the disease-affected proband and non-affected sibling followed by in silico predictions and a series of RNA-based assays clarifying variant functionality. By prioritizing variants obtained by genome sequencing, we discovered the novel deep intronic alteration APC:c.531 + 1482 A > G that was demonstrated to cause out-of-frame exonization of 56 base pairs from intron 5 of the gene. Further cDNA assays confirmed, that the aberrant splicing event was complete and its splice product was subject to nonsense-mediated decay. Co-segregation was observed between the variant carrier status and the disease phenotype. Cumulative evidence confirmed that APC:c.531 + 1482 A > G is a pathogenic variant causative of the disease.

Is HLA type a possible cancer risk modifier in Lynch syndrome?

Lynch syndrome (LS) is the most common inherited cancer syndrome. It is inherited via a monoallelic germline variant in one of the DNA mismatch repair (MMR) genes. LS carriers have a broad 30% to 80% risk of developing various malignancies, and more precise, individual risk estimations would be of high clinical value, allowing tailored cancer prevention and surveillance. Due to MMR deficiency, LS cancers are characterized by the accumulation of frameshift mutations leading to highly immunogenic frameshift peptides (FSPs). Thus, immune surveillance is proposed to inhibit the outgrowth of MMR-deficient cell clones. Recent studies have shown that immunoediting during the evolution of MMR-deficient cancers leads to a counter-selection of highly immunogenic antigens. The immunogenicity of FSPs is dependent on the antigen presentation. One crucial factor determining antigen presentation is the HLA genotype. Hence, a LS carrier's HLA genotype plays an important role in the presentation of FSP antigens to the immune system, and may influence the likelihood of progression from precancerous lesions to cancer. To address the challenge of clarifying this possibility including diverse populations with different HLA types, we have established the INDICATE initiative (Individual cancer risk by HLA type, http://indicate-lynch.org/), an international network aiming at a systematic evaluation of the HLA genotype as a possible cancer risk modifier in LS. Here we summarize the current knowledge on the role of HLA type in cancer risk and outline future research directions to delineate possible association in the scenario of LS with genetically defined risk population and highly immunogenic tumors.

A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins.

How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. Forty-eight percent of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure.

Discovering sex and age implicator edges in the human connectome.

Determining important vertices in large graphs (e.g., Google's PageRank in the case of the graph of the World Wide Web) facilitated the construction of excellent web search engines, returning the most important hits corresponding to the submitted user queries. Interestingly, finding important edges - instead of vertices - in large graphs has received much less attention until now. Here we examine the human structural braingraph (or connectome), identified by diffusion magnetic resonance imaging (dMRI) methods, with edges connecting cortical and subcortical gray matter areas and weighted by fiber strengths, measured by the number of the discovered fiber tracts along the edge. We identify several "single" important edges in these braingraphs, whose high or low weights imply the sex or the age of the subject observed. We call these edges implicator edges since solely from their weight, one can infer the sex of the subject with more than 67 % accuracy or their age group with more than 62% accuracy. We argue that these brain connections are the most important ones characterizing the sex or the age of the subjects. Surprisingly, the edges implying the male sex are mostly located in the anterior parts of the brain, while those implying the female sex are mostly in the posterior regions. Additionally, most of the inter-hemispheric implicator edges are male ones, while the intra-hemispheric ones are predominantly female edges. Our pioneering method for finding the sex- or age implicator edges can also be applied for characterizing other biological and medical properties, including neurodegenerative- and psychiatric diseases besides the sex or the age of the subject, if large and high-quality neuroimaging datasets become available. We emphasize that our contribution identifies statistically valid single brain connections related to the sex and the age of the subjects in a large and robust dataset. To our knowledge, our results are unprecedented in this aspect.

Succinct Amyloid and Nonamyloid Patterns in Hexapeptides.

Hexapeptides are widely applied as a model system for studying the amyloid-forming properties of polypeptides, including proteins. Recently, large experimental databases have become publicly available with amyloidogenic labels. Using these data sets for training and testing purposes, one may build artificial intelligence (AI)-based classifiers for predicting the amyloid state of peptides. In our previous work (Biomolecules 2021, 11, 500), we described the Support Vector Machine (SVM)-based Budapest Amyloid Predictor (https://pitgroup.org/bap). Here, we apply the Budapest Amyloid Predictor for discovering numerous amyloidogenic and nonamyloidogenic hexapeptide patterns with accuracy between 80% and 84%, as surprising and succinct novel rules for further understanding the amyloid state of peptides. For example, we have shown that for any independently mutated residue (position marked by "x"), the patterns CxFLWx, FxFLFx, or xxIVIV are predicted to be amyloidogenic, while those of PxDxxx, xxKxEx, and xxPQxx are nonamyloidogenic. We note that each amyloidogenic pattern with two x's (e.g.,CxFLWx) describes succinctly 202 = 400 hexapeptides, while the nonamyloidogenic patterns comprising four point mutations (e.g.,PxDxxx) give 204 = 160 000 hexapeptides in total. We also examine the restricted substitutions for positions "x" from subclasses of proteinogenic amino acid residues; for example, if "x" is substituted with hydrophobic amino acids, then there exist patterns containing three x's, like MxVVxx, predicted to be amyloidogenic. If we can choose for the x positions any hydrophobic amino acids, except the "structure breaker" proline, then we get amyloid patterns with five x positions, for example, xxxFxx, each corresponding to 32 768 hexapeptides. To our knowledge, no similar applications of artificial intelligence tools or succinct amyloid patterns were described before the present work.

Introducing and applying Newtonian blurring: an augmented dataset of 126,000 human connectomes at braingraph.org.

Gaussian blurring is a well-established method for image data augmentation: it may generate a large set of images from a small set of pictures for training and testing purposes for Artificial Intelligence (AI) applications. When we apply AI for non-imagelike biological data, hardly any related method exists. Here we introduce the "Newtonian blurring" in human braingraph (or connectome) augmentation: Started from a dataset of 1053 subjects from the public release of the Human Connectome Project, we first repeat a probabilistic weighted braingraph construction algorithm 10 times for describing the connections of distinct cerebral areas, then for every possible set of 7 of these graphs, delete the lower and upper extremes, and average the remaining 7 - 2 = 5 edge-weights for the data of each subject. This way we augment the 1053 graph-set to 120 [Formula: see text] 1053 = 126,360 graphs. In augmentation techniques, it is an important requirement that no artificial additions should be introduced into the dataset. Gaussian blurring and also this Newtonian blurring satisfy this goal. The resulting dataset of 126,360 graphs, each in 5 resolutions (i.e., 631,800 graphs in total), is freely available at the site https://braingraph.org/cms/download-pit-group-connectomes/ . Augmenting with Newtonian blurring may also be applicable in other non-image-related fields, where probabilistic processing and data averaging are implemented.

SCARF: a biomedical association rule finding webserver.

The analysis of enormous datasets with missing data entries is a standard task in biological and medical data processing. Large-scale, multi-institution clinical studies are the typical examples of such datasets. These sets make possible the search for multi-parametric relations since from the plenty of the data one is likely to find a satisfying number of subjects with the required parameter ensembles. Specifically, finding combinatorial biomarkers for some given condition also needs a very large dataset to analyze. For fast and automatic multi-parametric relation discovery association-rule finding tools are used for more than two decades in the data-mining community. Here we present the SCARF webserver for generalized association rule mining. Association rules are of the form: a AND b AND … AND x → y, meaning that the presence of properties a AND b AND … AND x implies property y; our algorithm finds generalized association rules, since it also finds logical disjunctions (i.e., ORs) at the left-hand side, allowing the discovery of more complex rules in a more compressed form in the database. This feature also helps reducing the typically very large result-tables of such studies, since allowing ORs in the left-hand side of a single rule could include dozens of classical rules. The capabilities of the SCARF algorithm were demonstrated in mining the Alzheimer's database of the Coalition Against Major Diseases (CAMD) in our recent publication (Archives of Gerontology and Geriatrics Vol. 73, pp. 300-307, 2017). Here we describe the webserver implementation of the algorithm.

Reclassification of Five BRCA1/2 Variants with Unknown Significance Using Complex Functional Study.

PURPOSE: While BRCA1/2 genes are commonly investigated, variants of unknown significance (VUS) and variants with potential splice effect are still being detected and they represent a substantial challenge in genetic counseling and therapy. MATERIALS AND METHODS: Out of genetically tested 3,568 hereditary breast and ovarian cancer probands five, functionally not investigated variants with potential splice-modifying effect were subjected to functional characterization. Transcript-level analysis on peripheral blood-derived RNA of the carriers was performed to test aberrant splicing. The completeness of the aberrant splicing event was also studied, existence and extent of nonsense-mediated decay was even addressed. Clinical and phenotype data, pedigree and co-segregation analyses were also done. Locus-specific loss of heterozygosity (LOH) in tumor tissues was additionally tested. RESULTS: In case of the BRCA1:c.4484+4dupA and the BRCA1:c.5407-10G>A variants functional results allowed us to reclassify them from VUS into likely pathogenic category. BRCA1:c.4358-31A>C, by producing incomplete aberrant splicing, was highlighted as strong VUS, but in lack of other supporting evidence, re-categorization was not possible. The likely pathogenic assertion of previously not reported BRCA2:c.8487G>T was reinforced based on its spliceogenic property and tumor LOH, while BRCA2:c.793G>A failed to present aberrant splicing in spite of suggestive predictions, which altered its original VUS evaluation into likely benign class. CONCLUSION: We presented molecular and clinical evidence for reclassification of four out of five BRCA1/2 variants. Both up- and down-classification harbour important clinical significance. Patients carrying re-classified pathogenic variants in the future will not be dropped out from medical surveillance, preventive measures, treatment and predictive family screening in relatives at risk.

Identifying super-feminine, super-masculine and sex-defining connections in the human braingraph.

For more than a decade now, we can discover and study thousands of cerebral connections with the application of diffusion magnetic resonance imaging (dMRI) techniques and the accompanying algorithmic workflow. While numerous connectomical results were published enlightening the relation between the braingraph and certain biological, medical, and psychological properties, it is still a great challenge to identify a small number of brain connections closely related to those conditions. In the present contribution, by applying the 1200 Subjects Release of the Human Connectome Project (HCP) and Support Vector Machines, we identify just 102 connections out of the total number of 1950 connections in the 83-vertex graphs of 1064 subjects, which-by a simple linear test-precisely, without any error determine the sex of the subject. Next, we re-scaled the weights of the edges-corresponding to the discovered fibers-to be between 0 and 1, and, very surprisingly, we were able to identify two graph edges out of these 102, such that, if their weights are both 1, then the connectome always belongs to a female subject, independently of the other edges. Similarly, we have identified 3 edges from these 102, whose weights, if two of them are 1 and one is 0, imply that the graph belongs to a male subject-again, independently of the other edges. We call the former 2 edges superfeminine and the first two of the 3 edges supermasculine edges of the human connectome. Even more interestingly, the edge, connecting the right Pars Triangularis and the right Superior Parietal areas, is one of the 2 superfeminine edges, and it is also the third edge, accompanying the two supermasculine connections if its weight is 0; therefore, it is also a "switching" edge. Identifying such edge-sets of distinction is the unprecedented result of this work. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11571-021-09687-w.

The braingraph.org database with more than 1000 robust human connectomes in five resolutions.

The human brain is the most complex object of study we encounter today. Mapping the neuronal-level connections between the more than 80 billion neurons in the brain is a hopeless task for science. By the recent advancement of magnetic resonance imaging (MRI), we are able to map the macroscopic connections between about 1000 brain areas. The MRI data acquisition and the subsequent algorithmic workflow contain several complex steps, where errors can occur. In the present contribution we describe and publish 1064 human connectomes, computed from the public release of the Human Connectome Project. Each connectome is available in 5 resolutions, with 83, 129, 234, 463 and 1015 anatomically labeled nodes. For error correction we follow an averaging and extreme value deleting strategy for each edge and for each connectome. The resulting 5320 braingraphs can be downloaded from the https://braingraph.org site. This dataset makes possible the access to this graphs for scientists unfamiliar with neuroimaging- and connectome-related tools: mathematicians, physicists and engineers can use their expertize and ideas in the analysis of the connections of the human brain. Brain scientists and computational neuroscientists also have a robust and large, multi-resolution set for connectomical studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11571-021-09670-5.