Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia.

The role of Hedgehog signaling in normal and malignant T-cell development is controversial. Recently, Hedgehog pathway mutations have been described in T-ALL, but whether mutational activation of Hedgehog signaling drives T-cell transformation is unknown, hindering the rationale for therapeutic intervention. Here, we show that Hedgehog pathway mutations predict chemotherapy resistance in human T-ALL, and drive oncogenic transformation in a zebrafish model of the disease. We found Hedgehog pathway mutations in 16% of 109 childhood T-ALL cases, most commonly affecting its negative regulator PTCH1. Hedgehog mutations were associated with resistance to induction chemotherapy (P = 0.009). Transduction of wild-type PTCH1 into PTCH1-mutant T-ALL cells induced apoptosis (P = 0.005), a phenotype that was reversed by downstream Hedgehog pathway activation (P = 0.007). Transduction of most mutant PTCH1, SUFU, and GLI alleles into mammalian cells induced aberrant regulation of Hedgehog signaling, indicating that these mutations are pathogenic. Using a CRISPR/Cas9 system for lineage-restricted gene disruption in transgenic zebrafish, we found that ptch1 mutations accelerated the onset of notch1-induced T-ALL (P = 0.0001), and pharmacologic Hedgehog pathway inhibition had therapeutic activity. Thus, Hedgehog-activating mutations are driver oncogenic alterations in high-risk T-ALL, providing a molecular rationale for targeted therapy in this disease

Targeted genetic testing for familial hypercholesterolaemia using next generation sequencing:a population-based study

Background<p></p> Familial hypercholesterolaemia (FH) is a common Mendelian condition which, untreated, results in premature coronary heart disease. An estimated 88% of FH cases are undiagnosed in the UK. We previously validated a method for FH mutation detection in a lipid clinic population using next generation sequencing (NGS), but this did not address the challenge of identifying index cases in primary care where most undiagnosed patients receive healthcare. Here, we evaluate the targeted use of NGS as a potential route to diagnosis of FH in a primary care population subset selected for hypercholesterolaemia.<p></p> Methods<p></p> We used microfluidics-based PCR amplification coupled with NGS and multiplex ligation-dependent probe amplification (MLPA) to detect mutations in LDLR, APOB and PCSK9 in three phenotypic groups within the Generation Scotland: Scottish Family Health Study including 193 individuals with high total cholesterol, 232 with moderately high total cholesterol despite cholesterol-lowering therapy, and 192 normocholesterolaemic controls.<p></p> Results<p></p> Pathogenic mutations were found in 2.1% of hypercholesterolaemic individuals, in 2.2% of subjects on cholesterol-lowering therapy and in 42% of their available first-degree relatives. In addition, variants of uncertain clinical significance (VUCS) were detected in 1.4% of the hypercholesterolaemic and cholesterol-lowering therapy groups. No pathogenic variants or VUCS were detected in controls.<p></p> Conclusions<p></p> We demonstrated that population-based genetic testing using these protocols is able to deliver definitive molecular diagnoses of FH in individuals with high cholesterol or on cholesterol-lowering therapy. The lower cost and labour associated with NGS-based testing may increase the attractiveness of a population-based approach to FH detection compared to genetic testing with conventional sequencing. This could provide one route to increasing the present low percentage of FH cases with a genetic diagnosis

Cataloging Coding Sequence Variations in Human Genome Databases

BACKGROUND: With the recent growth of information on sequence variations in the human genome, predictions regarding the functional effects and relevance to disease phenotypes of coding sequence variations are becoming increasingly important. The aims of this study were to catalog protein-coding sequence variations (CVs) occurring in genetic variation databases and to use bioinformatic programs to analyze CVs. In addition, we aim to provide insight into the functionality of the reference databases. METHODOLOGY AND FINDINGS: To catalog CVs on a genome-wide scale with regard to protein function and disease, we investigated three representative databases; the Human Gene Mutation Database (HGMD), the Single Nucleotide Polymorphisms database (dbSNP), and the Haplotype Map (HapMap). Using these three databases, we analyzed CVs at the protein function level with bioinformatic programs. We proposed a combinatorial approach using the Support Vector Machine (SVM) to increase the performance of the prediction programs. By cataloging the coding sequence variations using these databases, we found that 4.36% of CVs from HGMD are concurrently registered in dbSNP (8.11% of CVs from dbSNP are concurrent in HGMD). The pattern of substitutions and functional consequences predicted by three bioinformatic programs was significantly different among concurrent CVs, and CVs occurring solely in HGMD or in dbSNP. The experimental results showed that the proposed SVM combination noticeably outperformed the individual prediction programs. CONCLUSIONS: This is the first study to compare human sequence variations in HGMD, dbSNP and HapMap at the genome-wide level. We found that a significant proportion of CVs in HGMD and dbSNP overlap, and we emphasize the need to use caution when interpreting the phenotypic relevance of these concurrent CVs. Combining bioinformatic programs can be helpful in predicting the functional consequences of CVs because it improved the performance of functional predictions

Deriving a mutation index of carcinogenicity using protein structure and protein interfaces

With the advent of Next Generation Sequencing the identification of mutations in the genomes of healthy and diseased tissues has become commonplace. While much progress has been made to elucidate the aetiology of disease processes in cancer, the contributions to disease that many individual mutations make remain to be characterised and their downstream consequences on cancer phenotypes remain to be understood. Missense mutations commonly occur in cancers and their consequences remain challenging to predict. However, this knowledge is becoming more vital, for both assessing disease progression and for stratifying drug treatment regimes. Coupled with structural data, comprehensive genomic databases of mutations such as the 1000 Genomes project and COSMIC give an opportunity to investigate general principles of how cancer mutations disrupt proteins and their interactions at the molecular and network level. We describe a comprehensive comparison of cancer and neutral missense mutations; by combining features derived from structural and interface properties we have developed a carcinogenicity predictor, InCa (Index of Carcinogenicity). Upon comparison with other methods, we observe that InCa can predict mutations that might not be detected by other methods. We also discuss general limitations shared by all predictors that attempt to predict driver mutations and discuss how this could impact high-throughput predictions. A web interface to a server implementation is publicly available at http://inca.icr.ac.uk/

Do-it-yourself genetic testing

We developed a computational screen that tests an individual's genome for mutations in the BRCA genes, despite the fact that both are currently protected by patents

Towards personalised allele-specific CRISPR gene editing to treat autosomal dominant disorders

Abstract CRISPR/Cas9 holds immense potential to treat a range of genetic disorders. Allele-specific gene disruption induced by non-homologous end-joining (NHEJ) DNA repair offers a potential treatment option for autosomal dominant disease. Here, we successfully delivered a plasmid encoding S. pyogenes Cas9 and sgRNA to the corneal epithelium by intrastromal injection and acheived long-term knockdown of a corneal epithelial reporter gene, demonstrating gene disruption via NHEJ in vivo. In addition, we used TGFBI corneal dystrophies as a model of autosomal dominant disease to assess the use of CRISPR/Cas9 in two allele-specific systems, comparing cleavage using a SNP-derived PAM to a guide specific approach. In vitro, cleavage via a SNP-derived PAM was found to confer stringent allele-specific cleavage, while a guide-specific approach lacked the ability to distinguish between the wild-type and mutant alleles. The failings of the guide-specific approach highlights the necessity for meticulous guide design and assessment, as various degrees of allele-specificity are achieved depending on the guide sequence employed. A major concern for the use of CRISPR/Cas9 is its tendency to cleave DNA non-specifically at “off-target” sites. Confirmation that S. pyogenes Cas9 lacks the specificity to discriminate between alleles differing by a single base-pair regardless of the position in the guide is demonstrated

A Novel Splicing Mutation Alters DSPP Transcription and Leads to Dentinogenesis Imperfecta Type II

Dentinogenesis imperfecta (DGI) type II is an autosomal dominant disease characterized by a serious disorders in teeth. Mutations of dentin sialophosphoprotein (DSPP) gene were revealed to be the causation of DGI type II (DGI-II). In this study, we identified a novel mutation (NG_011595.1:g.8662T>C, c.135+2T>C) lying in the splice donor site of intron 3 of DSPP gene in a Chinese Han DGI-II pedigree. It was found in all affected subjects but not in unaffected ones or other unrelated healthy controls. The function of the mutant DSPP gene, which was predicted online and subsequently confirmed by in vitro splicing analysis, was the loss of splicing of intron 3, leading to the extended length of DSPP mRNA. For the first time, the functional non-splicing of intron was revealed in a novel DSPP mutation and was considered as the causation of DGI-II. It was also indicated that splicing was of key importance to the function of DSPP and this splice donor site might be a sensitive mutation hot spot. Our findings combined with other reports would facilitate the genetic diagnosis of DGI-II, shed light on its gene therapy and help to finally conquer human diseases

CADASIL in Arabs: clinical and genetic findings

<p>Abstract</p> <p>Background</p> <p>Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is increasingly recognized as an inherited arterial disease leading to a step-wise decline and eventually to dementia. CADASIL is caused by mutations in <it>NOTCH3 </it>epidermal growth factor-like repeat that maps to chromosome 19. CADASIL cases have been identified in most countries of Western and Central Europe, the Americas, Japan, Australia, the Caribbean, South America, Tanzania, Turkey, South Africa and Southeast Asia, but not in Arabs.</p> <p>Methods</p> <p>We studied three families from Saudi Arabia (Family A), Kuwait (Family B) and Yemen (Family C) with 19 individuals affected by CADASIL.</p> <p>Results</p> <p>The mean age of onset was 31 ± 6 and the clinical presentation included stroke in 68%, subcortical dementia in 17% and asymptomatic leukoariosis detected by MRI in 15%. Migraine and depression were frequently associated, 38% and 68% respectively. The mean age of death was 56 ± 11. All <it>NOTCH3 </it>exons were screened for mutations, which revealed the presence of previously reported mutations c.406C>T (p.Arg110>Cys) in two families (family A&B) and c.475C>T (p.Arg133>Cys) mutation in family C.</p> <p>Conclusion</p> <p>CADASIL occurs in Arabs, with clinical phenotype and genotype similar to that in other ethnic groups.</p

COSMIC 2005

The Catalogue Of Somatic Mutations In Cancer (COSMIC) database and web site was developed to preserve somatic mutation data and share it with the community. Over the past 25 years, approximately 350 cancer genes have been identified, of which 311 are somatically mutated. COSMIC has been expanded and now holds data previously reported in the scientific literature for 28 known cancer genes. In addition, there is data from the systematic sequencing of 518 protein kinase genes. The total gene count in COSMIC stands at 538; 25 have a mutation frequency above 5% in one or more tumour type, no mutations were found in 333 genes and 180 are rarely mutated with frequencies <5% in any tumour set. The COSMIC web site has been expanded to give more views and summaries of the data and provide faster query routes and downloads. In addition, there is a new section describing mutations found through a screen of known cancer genes in 728 cancer cell lines including the NCI-60 set of cancer cell lines

RNAseq Analyses Identify Tumor Necrosis Factor-Mediated Inflammation as a Major Abnormality in ALS Spinal Cord

ALS is a rapidly progressive, devastating neurodegenerative illness of adults that produces disabling weakness and spasticity arising from death of lower and upper motor neurons. No meaningful therapies exist to slow ALS progression, and molecular insights into pathogenesis and progression are sorely needed. In that context, we used high-depth, next generation RNA sequencing (RNAseq, Illumina) to define gene network abnormalities in RNA samples depleted of rRNA and isolated from cervical spinal cord sections of 7 ALS and 8 CTL samples. We aligned \u3e50 million 2X150 bp paired-end sequences/sample to the hg19 human genome and applied three different algorithms (Cuffdiff2, DEseq2, EdgeR) for identification of differentially expressed genes (DEG’s). Ingenuity Pathways Analysis (IPA) and Weighted Gene Co-expression Network Analysis (WGCNA) identified inflammatory processes as significantly elevated in our ALS samples, with tumor necrosis factor (TNF) found to be a major pathway regulator (IPA) and TNFα-induced protein 2 (TNFAIP2) as a major network “hub” gene (WGCNA). Using the oPOSSUM algorithm, we analyzed transcription factors (TF) controlling expression of the nine DEG/hub genes in the ALS samples and identified TF’s involved in inflammation (NFkB, REL, NFkB1) and macrophage function (NR1H2::RXRA heterodimer). Transient expression in human iPSC-derived motor neurons of TNFAIP2 (also a DEG identified by all three algorithms) reduced cell viability and induced caspase 3/7 activation. Using high-density RNAseq, multiple algorithms for DEG identification, and an unsupervised gene co-expression network approach, we identified significant elevation of inflammatory processes in ALS spinal cord with TNF as a major regulatory molecule. Overexpression of the DEG TNFAIP2 in human motor neurons, the population most vulnerable to die in ALS, increased cell death and caspase 3/7 activation. We propose that therapies targeted to reduce inflammatory TNFα signaling may be helpful in ALS patients