Germline Structural Variations in Cancer Predisposition Genes

Constitutional balanced translocations involving SMARCB1: A rare cause of rhabdoid tumor predisposition syndrome

Rhabdoid Tumor Predisposition Syndrome 1 (RTPS1) confers an increased risk of developing rhabdoid tumors and is caused by germline mutations in SMARCB1. RTPS1 should be evaluated in all individuals with rhabdoid tumor and is more likely in those with a young age at presentation (occasionally congenital presentation), multiple primary tumors, or a family history of rhabdoid tumor or RTPS1. Proband genetic testing is the standard method for diagnosing RTPS1. Most known RTPS1-related SMARCB1 gene mutations are copy number variants (CNVs) or single nucleotide variants/indels, but structural variant analysis (SVA) is not usually included in the molecular evaluation. Here, we report two children with RTPS1 presenting with atypical teratoid/rhabdoid tumor (ATRT) who had constitutional testing showing balanced chromosome translocations involving SMARCB1. Patient 1 is a 23-year-old female diagnosed with pineal region ATRT at 7 months who was found to have a de novo, constitutional t(16;22)(p13.3;q11.2). Patient 2 is a 24-month-old male diagnosed with a posterior fossa ATRT at 14 months, with subsequent testing showing a constitutional t(5;22)(q14.1;q11.23). These structural rearrangements have not been previously reported in RTPS1. While rare, these cases suggest that structural variants should be considered in the evaluation of children with rhabdoid tumors to provide more accurate genetic counseling on the risks of developing tumors, the need for surveillance, and the risks of passing the disorder on to future children. Further research is needed to understand the prevalence, clinical features, and tumor risks associated with RTPS1-related constitutional balanced translocations.

Genomics in Clinical trials for Breast Cancer

Breast cancer (B.C.) still has increasing incidences and mortality rates globally. It is known that B.C. and other cancers have a very high rate of genetic heterogeneity and genomic mutations. Traditional oncology approaches have not been able to provide a lasting solution. Targeted therapeutics have been instrumental in handling the complexity and resistance associated with B.C. However, the progress of genomic technology has transformed our understanding of the genetic landscape of breast cancer, opening new avenues for improved anti-cancer therapeutics. Genomics is critical in developing tailored therapeutics and identifying patients most benefit from these treatments. The next generation of breast cancer clinical trials has incorporated next-generation sequencing technologies into the process, and we have seen benefits. These innovations have led to the approval of better-targeted therapies for patients with breast cancer. Genomics has a role to play in clinical trials, including genomic tests that have been approved, patient selection and prediction of therapeutic response. Multiple clinical trials in breast cancer have been done and are still ongoing, which have applied genomics technology. Precision medicine can be achieved in breast cancer therapy with increased efforts and advanced genomic studies in this domain. Genomics studies assist with patient outcomes improvement and oncology advancement by providing a deeper understanding of the biology behind breast cancer. This article will examine the present state of genomics in breast cancer clinical trials.

A review of the pangenome: how it affects our understanding of genomic variation, selection and breeding in domestic animals?

As large-scale genomic studies have progressed, it has been revealed that a single reference genome pattern cannot represent genetic diversity at the species level. While domestic animals tend to have complex routes of origin and migration, suggesting a possible omission of some population-specific sequences in the current reference genome. Conversely, the pangenome is a collection of all DNA sequences of a species that contains sequences shared by all individuals (core genome) and is also able to display sequence information unique to each individual (variable genome). The progress of pangenome research in humans, plants and domestic animals has proved that the missing genetic components and the identification of large structural variants (SVs) can be explored through pangenomic studies. Many individual specific sequences have been shown to be related to biological adaptability, phenotype and important economic traits. The maturity of technologies and methods such as third-generation sequencing, Telomere-to-telomere genomes, graphic genomes, and reference-free assembly will further promote the development of pangenome. In the future, pangenome combined with long-read data and multi-omics will help to resolve large SVs and their relationship with the main economic traits of interest in domesticated animals, providing better insights into animal domestication, evolution and breeding. In this review, we mainly discuss how pangenome analysis reveals genetic variations in domestic animals (sheep, cattle, pigs, chickens) and their impacts on phenotypes and how this can contribute to the understanding of species diversity. Additionally, we also go through potential issues and the future perspectives of pangenome research in livestock and poultry.

Investigation of Chromosomal Structural Abnormalities in Patients With Undiagnosed Neurodevelopmental Disorders

Background: Structural variations (SVs) are various types of the genomic rearrangements encompassing at least 50 nucleotides. These include unbalanced gains or losses of DNA segments (copy number changes, CNVs), balanced rearrangements (such as inversion or translocations), and complex combinations of several distinct rearrangements. SVs are known to play a significant role in contributing to human genomic disorders by disrupting the protein-coding genes or the interaction(s) with cis-regulatory elements. Recently, different types of genome sequencing-based tests have been introduced in detecting various types of SVs other than CNVs and regions with absence of heterozygosity (AOH) with clinical significance.

Method: In this study, we applied the mate-pair low pass (∼4X) genome sequencing with large DNA-insert (∼5 kb) in a cohort of 100 patients with neurodevelopmental disorders who did not receive informative results from a routine CNV investigation. Read-depth-based CNV analysis and chimeric-read-pairs analysis were used for CNV and SV analyses. The region of AOH was indicated by a simultaneous decrease in the rate of heterozygous SNVs and increase in the rate of homozygous SNVs.

Results: First, we reexamined the 25 previously reported CNVs among 24 cases in this cohort. The boundaries of these twenty-five CNVs including 15 duplications and 10 deletions detected were consistent with the ones indicated by the chimeric-read-pairs analysis, while the location and orientation were determined in 80% of duplications (12/15). Particularly, one duplication was involved in complex rearrangements. In addition, among all the 100 cases, 10% of them were detected with rare or complex SVs (>10 Kb), and 3% were with multiple AOH (≥5 Mb) locating in imprinting chromosomes identified. In particular, one patient with an overall value of 214.5 Mb of AOH identified on 13 autosomal chromosomes suspected parental consanguinity.

Conclusion: In this study, mate-pair low-pass GS resolved a significant proportion of CNVs with inconclusive significance, and detected additional SVs and regions of AOH in patients with undiagnostic neurodevelopmental disorders. This approach complements the first-tier CNV analysis for NDDs, not only by increasing the resolution of CNV detection but also by enhancing the characterization of SVs and the discovery of potential causative regions (or genes) contributory to could be complex in composition NDDs.