Inferring ligand-receptor cellular networks from bulk and spatial transcriptomic datasets with BulkSignalR.

The study of cellular networks mediated by ligand-receptor interactions has attracted much attention recently owing to single-cell omics. However, rich collections of bulk data accompanied with clinical information exists and continue to be generated with no equivalent in single-cell so far. In parallel, spatial transcriptomic (ST) analyses represent a revolutionary tool in biology. A large number of ST projects rely on multicellular resolution, for instance the Visium™ platform, where several cells are analyzed at each location, thus producing localized bulk data. Here, we describe BulkSignalR, a R package to infer ligand-receptor networks from bulk data. BulkSignalR integrates ligand-receptor interactions with downstream pathways to estimate statistical significance. A range of visualization methods complement the statistics, including functions dedicated to spatial data. We demonstrate BulkSignalR relevance using different datasets, including new Visium liver metastasis ST data, with experimental validation of protein colocalization. A comparison with other ST packages shows the significantly higher quality of BulkSignalR inferences. BulkSignalR can be applied to any species thanks to its built-in generic ortholog mapping functionality.

Expanding the Spectrum of Sarcoma with an Internal Tandem Duplication of BCOR: A Non-Pediatric Nasosinusal Case.

INTRODUCTION: Undifferentiated small round-cell sarcomas with BCL6 corepressor (BCOR) alterations, such as an internal tandem duplication (ITD) within exon 15, are typically described as a pediatric group of Ewing-like small round-cell sarcomas. CASE PRESENTATION: In contrast to this notion, we report the case of a 71-year-old woman with a nasosinusal sarcoma featuring a BCOR ITD. To the best of our knowledge, this presence had not been previously documented in a sarcoma of the nasal and sinus cavities in an elderly patient. The identified duplication shares a similar minimal critical region as described in clear-cell sarcomas of the kidney in children. This alteration, located within the PCGF1 binding domain, is believed to disrupt the activity of PRC1.1. CONCLUSION: This case underscores the need for in-depth research into the molecular biology of these rare tumors and explores potential alternative treatment options. The patient achieved remission after two cycles of doxorubicin and cyclophosphamide chemotherapy, highlighting the promise of potential therapeutic options for BCOR ITD sarcomas.

A Bioinformatics Toolkit for Next-Generation Sequencing in Clinical Oncology.

Next-generation sequencing (NGS) has taken on major importance in clinical oncology practice. With the advent of targeted therapies capable of effectively targeting specific genomic alterations in cancer patients, the development of bioinformatics processes has become crucial. Thus, bioinformatics pipelines play an essential role not only in the detection and in identification of molecular alterations obtained from NGS data but also in the analysis and interpretation of variants, making it possible to transform raw sequencing data into meaningful and clinically useful information. In this review, we aim to examine the multiple steps of a bioinformatics pipeline as used in current clinical practice, and we also provide an updated list of the necessary bioinformatics tools. This resource is intended to assist researchers and clinicians in their genetic data analyses, improving the precision and efficiency of these processes in clinical research and patient care.

Differential Sensitivity of Germline and Somatic BRCA Variants to PARP Inhibitor in High-Grade Serous Ovarian Cancer.

PURPOSE: The introduction of PARP inhibitors (PARPis) as a treatment option for patients with high-grade serous ovarian cancer (HGSOC) modified the approach of BRCA testing worldwide. In this study, we aim to evaluate the impact of BRCA1 and BRCA2 variants on treatment response and survival outcomes in patients diagnosed in our institution. METHODS: A total of 805 HGSOC samples underwent BRCA1 and BRCA2 variant detection by using next-generation sequencing (NGS). Among them, a pathogenic alteration was detected in 104 specimens. Clinicopathological features and germline status were recovered, and alteration types were further characterized. The clinical significance of variant type in terms of response to chemotherapy and to PARPis as well as overall survival were evaluated using univariate analysis. RESULTS: In our cohort, 13.2% of the HGSOC samples harbored a pathogenic BRCA1 or BRCA2 variant, among which 58.7% were inherited. No difference was observed between germline and somatic variants in terms of the gene altered. Interestingly, patients with somatic variants only (no germline) demonstrated better outcomes under PARPi treatment compared to those with germline ones. CONCLUSION: The determination of the inheritance or acquisition of BRCA1 and BRCA2 alterations could provide valuable information for improving management strategies and predicting the outcome of patients with HGSOC.

SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics.

Single-cell transcriptomics offers unprecedented opportunities to infer the ligand-receptor (LR) interactions underlying cellular networks. We introduce a new, curated LR database and a novel regularized score to perform such inferences. For the first time, we try to assess the confidence in predicted LR interactions and show that our regularized score outperforms other scoring schemes while controlling false positives. SingleCellSignalR is implemented as an open-access R package accessible to entry-level users and available from https://github.com/SCA-IRCM. Analysis results come in a variety of tabular and graphical formats. For instance, we provide a unique network view integrating all the intercellular interactions, and a function relating receptors to expressed intracellular pathways. A detailed comparison of related tools is conducted. Among various examples, we demonstrate SingleCellSignalR on mouse epidermis data and discover an oriented communication structure from external to basal layers.

Determination of the Optimal Bacterial DNA Extraction Method to Explore the Urinary Microbiota.

Recent advances in molecular biology have been successfully applied to the exploration of microbiota from various fluids. However, the urinary microbiota remains poorly explored, as its analysis requires specific technical considerations. Indeed, urine is a low microbial biomass environment, in which the representativity of each bacterium must be respected to obtain accurate data. Thus, sensitive extraction methods must be used to obtain good quality DNA while preserving the proportions between species. To address this, we compared the efficiency of five extraction methods on artificial urine samples spiked with low amounts of four bacteria species. The quality of the DNA obtained was further evaluated by different molecular biology approaches, including quantitative PCR and amplicon-based next-generation sequencing (NGS). Although two extraction methods allowed DNA of sufficient quality for NGS analysis to be obtained, one kit extracted a larger amount of DNA, which is more suitable for the detection of low-abundant bacteria. Results from the subsequent assessment of this kit on 29 human clinical samples correlated well with results obtained using conventional bacterial urine culture. We hope that our work will make investigators aware of the importance of challenging and adapting their practice in terms of the molecular biology approaches used for the exploration of microbiota.

Dynamics of polymer nanoparticles through a single artificial nanopore with a high-aspect-ratio.

The development of nanometric Coulter counters for nanoparticle detection is an attractive and promising field of research. In this work, we have studied the influence of the nanopore surface state on charged polymer nanoparticle translocations. To make this, the translocation of carboxylate modified polystyrene microspheres (diameter 40, 70 and 100 nm) has been investigated through two kinds of high aspect ratio nanopores (negative and uncharged). The latter were tailored by a single track-etched and atomic layer deposition technique. It was shown that the mobility and the energy barrier are strongly dependent on nanopore surface charge. Typically if the latter exhibits negative surface charge, the microsphere mobility increases and the global energy barrier of entrance inside the nanopore decreases with its diameter, converse to the uncharged nanopore.

Characterizing PALB2 intragenic duplication breakpoints in a triple-negative breast cancer case using long-read sequencing.

Introduction: Accurate identification and characterization of Large Genomic Rearrangements (LGR), especially duplications, are crucial for precise diagnosis and risk assessment. In this report, we characterized an intragenic duplication breakpoint of PALB2 to determine its pathogenicity significance. Methods: A 52-year-old female with triple-negative breast cancer was diagnosed with a novel PALB2 LGR. An efficient and accurate methodology was applied, combining long-read sequencing and transcript analysis for the rapid characterization of the duplication. Results: Duplication of exons 5 and 6 of PALB2 was validated by transcript analysis. Long-read sequencing enabled the localization of breakpoints within Alu elements, providing insights into the mechanism of duplication via non-allelic homologous recombination. Conclusion: Using our combined methodology, we reclassified the PALB2 duplication as a pathogenic variant. This reclassification suggests a possible causative link between this specific genetic alteration and the aggressive phenotype of the patient.

ifCNV: A novel isolation-forest-based package to detect copy-number variations from various targeted NGS datasets.

Copy-number variations (CNVs) are an essential component of genetic variation distributed across large parts of the human genome. CNV detection from next-generation sequencing data and artificial intelligence algorithms have progressed in recent years. However, only a few tools have taken advantage of machine-learning algorithms for CNV detection, and none propose using artificial intelligence to automatically detect probable CNV-positive samples. The most developed approach is to use a reference or normal dataset to compare with the samples of interest, and it is well known that selecting appropriate normal samples represents a challenging task that dramatically influences the precision of results in all CNV-detecting tools. With careful consideration of these issues, we propose here ifCNV, a new software based on isolation forests that creates its own reference, available in R and python with customizable parameters. ifCNV combines artificial intelligence using two isolation forests and a comprehensive scoring method to faithfully detect CNVs among various samples. It was validated using targeted next-generation sequencing (NGS) datasets from diverse origins (capture and amplicon, germline and somatic), and it exhibits high sensitivity, specificity, and accuracy. ifCNV is a publicly available open-source software (https://github.com/SimCab-CHU/ifCNV) that allows the detection of CNVs in many clinical situations.

The molecular landscape and microenvironment of salivary duct carcinoma reveal new therapeutic opportunities.

Purpose: Salivary duct carcinoma (SDC) is a rare and aggressive salivary gland cancer subtype with poor prognosis. The mutational landscape of SDC has already been the object of several studies, however little is known regarding the functional genomics and the tumor microenvironment despite their importance in oncology. Our investigation aimed at describing both the functional genomics of SDC and the SDC microenvironment, along with their clinical relevance. Methods: RNA-sequencing (24 tumors), proteomics (17 tumors), immunohistochemistry (22 tumors), and multiplexed immunofluorescence (3 tumors) data were obtained from three different patient cohorts and analyzed by digital imaging and bioinformatics. Adjacent non-tumoral tissue from patients in two cohorts were used in transcriptomic and proteomic analyses. Results: Transcriptomic and proteomic data revealed the importance of Notch, TGF-ß, and interferon-γ signaling for all SDCs. We confirmed an overall strong desmoplastic reaction by measuring α-SMA abundance, the level of which was associated with recurrence-free survival (RFS). Two distinct immune phenotypes were observed: immune-poor SDCs (36%) and immune-infiltrated SDCs (64%). Advanced bioinformatics analysis of the transcriptomic data suggested 72 ligand-receptor interactions occurred in the microenvironment and correlated with the immune phenotype. Among these interactions, three immune checkpoints were validated by immunofluorescence, including CTLA-4/DC86 and TIM-3/galectin-9 interactions, previously unidentified in SDC. Immunofluorescence analysis also confirmed an important immunosuppressive role of macrophages and NK cells, also supported by the transcriptomic data. Conclusions: Together our data significantly increase the understanding of SDC biology and open new perspectives for SDC tumor treatment. Before applying immunotherapy, patient stratification according to the immune infiltrate should be taken into account. Immune-infiltrated SDC could benefit from immune checkpoint-targeting therapy, with novel options such as anti-CTLA-4. Macrophages or NK cells could also be targeted. The dense stroma, i.e., fibroblasts or hyaluronic acid, may also be the focus for immune-poor SDC therapies, e.g. in combination with Notch or TGF-ß inhibitors, or molecules targeting SDC mutations.

Ionic transport through sub-10 nm diameter hydrophobic high-aspect ratio nanopores: experiment, theory and simulation.

Fundamental understanding of ionic transport at the nanoscale is essential for developing biosensors based on nanopore technology and new generation high-performance nanofiltration membranes for separation and purification applications. We study here ionic transport through single putatively neutral hydrophobic nanopores with high aspect ratio (of length L = 6 µm with diameters ranging from 1 to 10 nm) and with a well controlled cylindrical geometry. We develop a detailed hybrid mesoscopic theoretical approach for the electrolyte conductivity inside nanopores, which considers explicitly ion advection by electro-osmotic flow and possible flow slip at the pore surface. By fitting the experimental conductance data we show that for nanopore diameters greater than 4 nm a constant weak surface charge density of about 10(-2) C m(-2) needs to be incorporated in the model to account for conductance plateaus of a few pico-siemens at low salt concentrations. For tighter nanopores, our analysis leads to a higher surface charge density, which can be attributed to a modification of ion solvation structure close to the pore surface, as observed in the molecular dynamics simulations we performed.

Diffusion tensor imaging differentiates vascular parkinsonism from parkinsonian syndromes of degenerative origin in elderly subjects.

BACKGROUND AND PURPOSE: The etiologic diagnosis of parkinsonian syndromes is of particular importance when considering syndromes of vascular or degenerative origin. The purpose of this study is to find differences in the white-matter architecture between those two groups in elderly patients. MATERIALS AND METHODS: Thirty-five patients were prospectively included (multiple-system atrophy, n=5; Parkinson's disease, n=15; progressive supranuclear palsy, n=9; vascular parkinsonism, n=6), with a mean age of 76 years. Patients with multiple-system atrophy, progressive supranuclear palsy and Parkinson's disease were grouped as having parkinsonian syndromes of degenerative origin. Brain MRIs included diffusion tensor imaging. Fractional anisotropy and mean-diffusivity maps were spatially normalized, and group analyses between parkinsonian syndromes of degenerative origin and vascular parkinsonism were performed using a voxel-based approach. RESULTS: Statistical parametric-mapping analysis of diffusion tensor imaging data showed decreased fractional anisotropy value in internal capsules bilaterally in patients with vascular parkinsonism compared to parkinsonian syndromes of degenerative origin (p=0.001) and showed a lower mean diffusivity in the white matter of the left superior parietal lobule (p=0.01). Fractional anisotropy values were found decreased in the middle cerebellar peduncles in multiple-system atrophy compared to Parkinson's disease and progressive supranuclear palsy. The mean diffusivity was increased in those regions for these subgroups. CONCLUSION: Clinically defined vascular parkinsonism was associated with decreased fractional anisotropy in the deep white matter (internal capsules) compared to parkinsonian syndromes of degenerative origin. These findings are consistent with previously published neuropathological data.

Slow translocation of polynucleotides and their discrimination by α-hemolysin inside a single track-etched nanopore designed by atomic layer deposition.

We report the formation of a hybrid biological/artificial nanopore by the direct insertion of non-modified α-hemolysin at the entrance of a high aspect ratio (length/diameter) biomimetic nanopore. In this robust hybrid system, the protein exhibits the same polynucleotide discrimination properties as in the biological membrane and the polynucleotide dwell time is strongly increased. This nanopore is very promising for DNA sequencing applications where the high DNA translocation velocity and the fragility of the support are the main bottlenecks.