Somatic mutations enriched in cis-regulatory elements affect genes involved in embryonic development and immune system response in neuroblastoma

Identification of novel genetic loci related to dromedary camel (Camelus dromedarius) morphometrics, biomechanics, and behavior by genome-wide association studies

In the realm of animal breeding for sustainability, domestic camels have traditionally been valued for their milk and meat production. However, key aspects such as zoometrics, biomechanics, and behavior have often been overlooked in terms of their genetic foundations. Recognizing this gap, the present study perfomed genome-wide association analyses to identify genetic markers associated with zoometrics-, biomechanics-, and behavior-related traits in dromedary camels (Camelus dromedarius). 16 and 108 genetic markers were significantly associated (q < 0.05) at genome and chromosome-wide levels of significance, respectively, with zoometrics- (width, length, and perimeter/girth), biomechanics- (acceleration, displacement, spatial position, and velocity), and behavior-related traits (general cognition, intelligence, and Intelligence Quotient (IQ)) in dromedaries. In most association loci, the nearest protein-coding genes are linkedto neurodevelopmental and sensory disorders. This suggests that genetic variations related to neural development and sensory perception play crucial roles in shaping a dromedary camel's physical characteristics and behavior. In summary, this research advances our understanding of the genomic basis of essential traits in dromedary camels. Identifying specific genetic markers associated with zoometrics, biomechanics, and behavior provides valuable insights into camel domestication. Moreover, the links between these traits and genes related to neurodevelopmental and sensory disorders highlight the broader implications of domestication and modern selection on the health and welfare of dromedary camels. This knowledge could guide future breeding strategies, fostering a more holistic approach to camel husbandry and ensuring the sustainability of these animals in diverse agricultural contexts.

Integrative genomic analyses identify neuroblastoma risk genes involved in neuronal differentiation

Genome-Wide Association Studies (GWAS) have been decisive in elucidating the genetic predisposition of neuroblastoma (NB). The majority of genetic variants identified in GWAS are found in non-coding regions, suggesting that they can be causative of pathogenic dysregulations of gene expression. Nonetheless, pinpointing the potential causal genes within implicated genetic loci remains a major challenge. In this study, we integrated NB GWAS and expression Quantitative Trait Loci (eQTL) data from adrenal gland to identify candidate genes impacting NB susceptibility. We found that ZMYM1, CBL, GSKIP and WDR81 expression was dysregulated by NB predisposing variants. We further investigated the functional role of the identified genes through computational analysis of RNA sequencing (RNA-seq) data from single-cell and whole-tissue samples of NB, neural crest, and adrenal gland tissues, as well as through in vitro differentiation assays in NB cell cultures. Our results indicate that dysregulation of ZMYM1, CBL, GSKIP, WDR81 may lead to malignant transformation by affecting early and late stages of normal program of neuronal differentiation. Our findings enhance the understanding of how specific genes contribute to NB pathogenesis by highlighting their influence on neuronal differentiation and emphasizing the impact of genetic risk variants on the regulation of genes involved in critical biological processes.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

From the identification of actionable molecular targets to the generation of faithful neuroblastoma patient-derived preclinical models

BACKGROUND

Neuroblastoma (NB) represents the most frequent and aggressive form of extracranial solid tumor of infants. Although the overall survival of patients with NB has improved in the last years, more than 50% of high-risk patients still undergo a relapse. Thus, in the era of precision/personalized medicine, the need for high-risk NB patient-specific therapies is urgent.

METHODS

Within the PeRsonalizEd Medicine (PREME) program, patient-derived NB tumors and bone marrow (BM)-infiltrating NB cells, derived from either iliac crests or tumor bone lesions, underwent to histological and to flow cytometry immunophenotyping, respectively. BM samples containing a NB cells infiltration from 1 to 50 percent, underwent to a subsequent NB cells enrichment using immune-magnetic manipulation. Then, NB samples were used for the identification of actionable targets and for the generation of 3D/tumor-spheres and Patient-Derived Xenografts (PDX) and Cell PDX (CPDX) preclinical models.

RESULTS

Eighty-four percent of NB-patients showed potentially therapeutically targetable somatic alterations (including point mutations, copy number variations and mRNA over-expression). Sixty-six percent of samples showed alterations, graded as "very high priority", that are validated to be directly targetable by an approved drug or an investigational agent. A molecular targeted therapy was applied for four patients, while a genetic counseling was suggested to two patients having one pathogenic germline variant in known cancer predisposition genes. Out of eleven samples implanted in mice, five gave rise to (C)PDX, all preserved in a local PDX Bio-bank. Interestingly, comparing all molecular alterations and histological and immunophenotypic features among the original patient's tumors and PDX/CPDX up to second generation, a high grade of similarity was observed. Notably, also 3D models conserved immunophenotypic features and molecular alterations of the original tumors.

CONCLUSIONS

PREME confirms the possibility of identifying targetable genomic alterations in NB, indeed, a molecular targeted therapy was applied to four NB patients. PREME paves the way to the creation of clinically relevant repositories of faithful patient-derived (C)PDX and 3D models, on which testing precision, NB standard-of-care and experimental medicines.

Phenotyping neuroblastoma cells through intelligent scrutiny of stain-free biomarkers in holographic flow cytometry

To efficiently tackle certain tumor types, finding new biomarkers for rapid and complete phenotyping of cancer cells is highly demanded. This is especially the case for the most common pediatric solid tumor of the sympathetic nervous system, namely, neuroblastoma (NB). Liquid biopsy is in principle a very promising tool for this purpose, but usually enrichment and isolation of circulating tumor cells in such patients remain difficult due to the unavailability of universal NB cell-specific surface markers. Here, we show that rapid screening and phenotyping of NB cells through stain-free biomarkers supported by artificial intelligence is a viable route for liquid biopsy. We demonstrate the concept through a flow cytometry based on label-free holographic quantitative phase-contrast microscopy empowered by machine learning. In detail, we exploit a hierarchical decision scheme where at first level NB cells are classified from monocytes with 97.9% accuracy. Then we demonstrate that different phenotypes are discriminated within NB class. Indeed, for each cell classified as NB its belonging to one of four NB sub-populations (i.e., CHP212, SKNBE2, SHSY5Y, and SKNSH) is evaluated thus achieving accuracy in the range 73.6%-89.1%. The achieved results solve the realistic problem related to the identification circulating tumor cell, i.e., the possibility to recognize and detect tumor cells morphologically similar to blood cells, which is the core issue in liquid biopsy based on stain-free microscopy. The presented approach operates at lab-on-chip scale and emulates real-world scenarios, thus representing a future route for liquid biopsy by exploiting intelligent biomedical imaging.

Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data.

Profiling and targeting cancer stem cell signaling pathways for cancer therapeutics

Tumorigenic cancer stem cells (CSCs) represent a subpopulation of cells within the tumor that express genetic and phenotypic profiles and signaling pathways distinct from the other tumor cells. CSCs have eluded many conventional anti-oncogenic treatments, resulting in metastases and relapses of cancers. Effectively targeting CSCs' unique self-renewal and differentiation properties would be a breakthrough in cancer therapy. A better characterization of the CSCs' unique signaling mechanisms will improve our understanding of the pathology and treatment of cancer. In this paper, we will discuss CSC origin, followed by an in-depth review of CSC-associated signaling pathways. Particular emphasis is given on CSC signaling pathways' ligand-receptor engagement, upstream and downstream mechanisms, and associated genes, and molecules. Signaling pathways associated with regulation of CSC development stand as potential targets of CSC therapy, which include Wnt, TGFβ (transforming growth factor-β)/SMAD, Notch, JAK-STAT (Janus kinase-signal transducers and activators of transcription), Hedgehog (Hh), and vascular endothelial growth factor (VEGF). Lastly, we will also discuss milestone discoveries in CSC-based therapies, including pre-clinical and clinical studies featuring novel CSC signaling pathway cancer therapeutics. This review aims at generating innovative views on CSCs toward a better understanding of cancer pathology and treatment.

Inherited rare variants in homologous recombination and neurodevelopmental genes are associated with increased risk of neuroblastoma

BACKGROUND

Neuroblastoma (NB) is the most common solid extracranial paediatric tumour. Genome-wide association studies have driven the discovery of common risk variants, but no large study has investigated the contribution of rare variants to NB susceptibility. Here, we conducted a whole-exome sequencing (WES) of 664 NB cases and 822 controls and used independent validation datasets to identify genes with rare risk variants and involved pathways.

METHODS

WES was performed at 50× depth and variants were jointly called in cases and controls. We developed two models to identify mutations with high clinical impact (P/LP model) and to discover less penetrant risk mutations affecting non-canonical cancer pathways (RPV model). We performed a gene-level collapsing test using Firth's logistic regression in 242 selected cancer predisposition genes (CPGs) and a gene-sets burden analysis of biologically-informed pathways.

FINDINGS

Twelve percent of patients carried P/LP variants in CPGs and showed a significant enrichment (P = 2.3 × 10^-4) compared to controls (6%). We identified P/LP variants in 45 CPGs enriched in homologous recombination (HR) pathway. The most P/LP enriched genes in NB were BRCA1, ALK and RAD51C. Additionally, we found higher RPV burden in gene-sets of neuron differentiation, neural tube development and synapse assembly, and in gene-sets associated with neurodevelopmental disorders (NDD).

INTERPRETATION

The high fraction of NB patients with P/LP variants indicates the need of genetic counselling. Furthermore, inherited rare variants predispose to NB development by affecting mechanisms related to HR and neurodevelopmental processes, and demonstrate that NDD genes are altered in NB at the germline level.

FUNDING

Associazione Italiana per la Ricerca sul Cancro, Fondazione Italiana per la Lotta al Neuroblastoma, Associazione Oncologia Pediatrica e Neuroblastoma, Regione Campania, Associazione Giulio Adelfio onlus, and Italian Health Ministry.

Single-cell transcriptomics of neuroblastoma identifies chemoresistance-associated genes and pathways

High-Risk neuroblastoma (NB) survival rate is still <50%, despite treatments being more and more aggressive. The biggest hurdle liable to cancer therapy failure is the drug resistance by tumor cells that is likely due to the intra-tumor heterogeneity (ITH). To investigate the link between ITH and therapy resistance in NB, we performed a single cell RNA sequencing (scRNAseq) of etoposide and cisplatin resistant NB and their parental cells. Our analysis showed a clear separation of resistant and parental cells for both conditions by identifying 8 distinct tumor clusters in etoposide-resistant/parental and 7 in cisplatin-resistant/parental cells. We discovered that drug resistance can affect NB cell identities; highlighting the bi-directional ability of adrenergic-to-mesenchymal transition of NB cells. The biological processes driving the identified resistant cell subpopulations revealed genes such as (BARD1, BRCA1, PARP1, HISTH1 axis, members of RPL family), suggesting a potential drug resistance due to the acquisition of DNA repair mechanisms and to the modification of the drug targets. Deconvolution analysis of bulk RNAseq data from 498 tumors with cell subpopulation signatures showed that the transcriptional heterogeneity of our cellular models reflected the ITH of NB tumors and allowed the identification of clusters associated with worse/better survival.

Our study demonstrates the distinct cell populations characterized by genes involved in different biological processes can have a role in NB drug treatment failure. These findings evidence the importance of ITH in NB drug resistance studies and the chance that scRNA-seq analysis offers in the identification of genes and pathways liable for drug resistance.