Haplotype-resolved germline and somatic alterations in renal medullary carcinomas

Background Renal medullary carcinomas (RMCs) are rare kidney cancers that occur in adolescents and young adults of African ancestry. Although RMC is associated with the sickle cell trait and somatic loss of the tumor suppressor, SMARCB1, the ancestral origins of RMC remain unknown. Further, characterization of structural variants (SVs) involving SMARCB1 in RMC remains limited. Methods We used linked-read genome sequencing to reconstruct germline and somatic haplotypes in 15 unrelated patients with RMC registered on the Children’s Oncology Group (COG) AREN03B2 study between 2006 and 2017 or from our prior study. We performed fine-mapping of the HBB locus and assessed the germline for cancer predisposition genes. Subsequently, we assessed the tumor samples for mutations outside of SMARCB1 and integrated RNA sequencing to interrogate the structural variants at the SMARCB1 locus. Results We find that the haplotype of the sickle cell mutation in patients with RMC originated from three geographical regions in Africa. In addition, fine-mapping of the HBB locus identified the sickle cell mutation as the sole candidate variant. We further identify that the SMARCB1 structural variants are characterized by blunt or 1-bp homology events. Conclusions Our findings suggest that RMC does not arise from a single founder population and that the HbS allele is a strong candidate germline allele which confers risk for RMC. Furthermore, we find that the SVs that disrupt SMARCB1 function are likely repaired by non-homologous end-joining. These findings highlight how haplotype-based analyses using linked-read genome sequencing can be applied to identify potential risk variants in small and rare disease cohorts and provide nucleotide resolution to structural variants.

Correction of the Sickle Cell Mutation Through Base and Prime Editing in Hematopoietic Stem Cells

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

p53: An Attractive Therapeutic Target for Cancer

Cancer is a leading cause of death worldwide. It initiates when cell cycle regulatory genes lose their function either by environmental and/or by internal factors. Tumor suppressor protein p53, known as “Guardian of genome”, plays a central role in maintaining genomic stability of the cell. Mutation of TP53 is documented in more than 50% of human cancers, usually by overexpression of negative regulator protein MDM2. Hence, reactivation of p53 by blocking the protein-protein interaction between the murine double minute 2 (MDM2) and the tumor suppressor protein p53 has become the most promising therapeutic strategy in oncology. Several classes of small molecules have been identified as potent, selective and efficient p53-MDM2 inhibitors. Herein, we review the druggability of p53-MDM2 inhibitors and their optimization approaches as well as clinical candidates categorized by scaffold type.

BnpC: Bayesian non-parametric clustering of single-cell mutation profiles

Motivation The high resolution of single-cell DNA sequencing (scDNA-seq) offers great potential to resolve intratumor heterogeneity (ITH) by distinguishing clonal populations based on their mutation profiles. However, the increasing size of scDNA-seq datasets and technical limitations, such as high error rates and a large proportion of missing values, complicate this task and limit the applicability of existing methods. Results Here, we introduce BnpC, a novel non-parametric method to cluster individual cells into clones and infer their genotypes based on their noisy mutation profiles. We benchmarked our method comprehensively against state-of-the-art methods on simulated data using various data sizes, and applied it to three cancer scDNA-seq datasets. On simulated data, BnpC compared favorably against current methods in terms of accuracy, runtime and scalability. Its inferred genotypes were the most accurate, especially on highly heterogeneous data, and it was the only method able to run and produce results on datasets with 5000 cells. On tumor scDNA-seq data, BnpC was able to identify clonal populations missed by the original cluster analysis but supported by Supplementary Experimental Data. With ever growing scDNA-seq datasets, scalable and accurate methods such as BnpC will become increasingly relevant, not only to resolve ITH but also as a preprocessing step to reduce data size. Availability and implementation BnpC is freely available under MIT license at https://github.com/cbg-ethz/BnpC. Supplementary information Supplementary data are available at Bioinformatics online.

Bile acids are a risk factor for colorectal cancer

Bile acids were first considered carcinogenic in 1939. Since then, accumulated data have associated colon cell changes with high levels of bile acids as an important risk factor for developing colorectal cancer, which is more common among people who consume large amounts of dietary fat. Secondary bile acids formed under the influence of the intestinal microbiota can cause the formation of reactive forms of oxygen and nitrogen, disruption of the cell membrane, mitochondria, DNA damage, reduction of apoptosis, increased cell mutation, turning them into cancer cells. High-fat diet, intestinal microflora, bile acids are a risk factors for colorectal cancer.