Michelle T. Dimon

Combined targeting of MEK and PI3K/mTOR effector pathways is necessary to effectively inhibit NRAS mutant melanoma in vitro and in vivo

Activating mutations in the neuroblastoma rat sarcoma viral oncogene homolog (NRAS) gene are common genetic events in malignant melanoma being found in 15–25% of cases. NRAS is thought to activate both mitogen activated protein kinase (MAPK) and PI3K signaling in melanoma cells. We studied the influence of different components on the MAP/extracellular signal-regulated (ERK) kinase (MEK) and PI3K/mammalian target of rapamycin (mTOR)-signaling cascade in NRAS mutant melanoma cells. In general, these cells were more sensitive to MEK inhibition compared with inhibition in the PI3K/mTOR cascade. Combined targeting of MEK and PI3K was superior to MEK and mTOR1,2 inhibition in all NRAS mutant melanoma cell lines tested, suggesting that PI3K signaling is more important for cell survival in NRAS mutant melanoma when MEK is inhibited. However, targeting of PI3K/mTOR1,2 in combination with MEK inhibitors is necessary to effectively abolish growth of NRAS mutant melanoma cells in vitro and regress xenografted NRAS mutant melanoma. Furthermore, we showed that MEK and PI3K/mTOR1,2 inhibition is synergistic. Expression analysis confirms that combined MEK and PI3K/mTOR1,2 inhibition predominantly influences genes in the rat sarcoma (RAS) pathway and growth factor receptor pathways, which signal through MEK/ERK and PI3K/mTOR, respectively. Our results suggest that combined targeting of the MEK/ERK and PI3K/mTOR pathways has antitumor activity and might serve as a therapeutic option in the treatment of NRAS mutant melanoma, for which there are currently no effective therapies.

NOTCH1 Mutations Occur Early during Cutaneous Squamous Cell Carcinogenesis

Cutaneous SCC (cSCC) is the most frequent skin cancer with metastatic potential and can manifest rapidly as a common side effect in patients receiving systemic kinase inhibitors. Here we use massively parallel exome and targeted level sequencing 132 sporadic cSCC, 39 squamoproliferative lesions and cSCC arising in patients receiving the BRAF inhibitor vemurafenib, as well as 10 normal skin samples to identify significant NOTCH1 mutation as an early event in squamous cell carcinogenesis. Bisected vemurafenib induced lesions revealed surprising heterogeneity with different activating HRAS and NOTCH1 mutations identified in two halves of the same cSCC suggesting polyclonal origin. Immunohistochemical analysis using an antibody specific to nuclear NOTCH1 correlates with mutation status in sporadic cSCC and regions of NOTCH1 loss or down-regulation are frequently observed in normal looking skin. Our data indicate that NOTCH1 acts as a gatekeeper in human cSCC.

RNA-Seq analysis of splicing in Plasmodium falciparum uncovers new splice junctions, alternative splicing and splicing of antisense transcripts

Over 50% of genes in Plasmodium falciparum, the deadliest human malaria parasite, contain predicted introns, yet experimental characterization of splicing in this organism remains incomplete. We present here a transcriptome-wide characterization of intraerythrocytic splicing events, as captured by RNA-Seq data from four timepoints of a single highly synchronous culture. Gene model-independent analysis of these data in conjunction with publically available RNA-Seq data with HMMSplicer, an in-house developed splice site detection algorithm, revealed a total of 977 new 5′ GU-AG 3′ and 5 new 5′ GC-AG 3′ junctions absent from gene models and ESTs (11% increase to the current annotation). In addition, 310 alternative splicing events were detected in 254 (4.5%) genes, most of which truncate open reading frames. Splicing events antisense to gene models were also detected, revealing complex transcriptional arrangements within the parasite’s transcriptome. Interestingly, antisense introns overlap sense introns more than would be expected by chance, perhaps indicating a functional relationship between overlapping transcripts or an inherent organizational property of the transcriptome. Independent experimental validation confirmed over 30 new antisense and alternative junctions. Thus, this largest assemblage of new and alternative splicing events to date in Plasmodium falciparum provides a more precise, dynamic view of the parasite’s transcriptome.

HMMSplicer: A Tool for Efficient and Sensitive Discovery of Known and Novel Splice Junctions in RNA-Seq Data

Background High-throughput sequencing of an organisms transcriptome, or RNA-Seq, is a valuable and versatile new strategy for capturing snapshots of gene expression. However, transcriptome sequencing creates a new class of alignment problem: mapping short reads that span exon-exon junctions back to the reference genome, especially in the case where a splice junction is previously unknown. Methodology/Principal Findings Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. Conclusions/Significance HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on pre-built gene models, the products of inexact splicing are also detected. For H. sapiens, we find 3.6% of 3′ splice sites and 1.4% of 5′ splice sites are inexact, typically differing by 3 bases in either direction. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available at http://derisilab.ucsf.edu/software/hmmsplicer.

The Long March: A Sample Preparation Technique that Enhances Contig Length and Coverage by High- Throughput Short-Read Sequencing

High-throughput short-read technologies have revolutionized DNA sequencing by drastically reducing the cost per base of sequencing information. Despite producing gigabases of sequence per run, these technologies still present obstacles in resequencing and de novo assembly applications due to biased or insufficient target sequence coverage. We present here a simple sample preparation method termed the “long march” that increases both contig lengths and target sequence coverage using high-throughput short-read technologies. By incorporating a Type IIS restriction enzyme recognition motif into the sequencing primer adapter, successive rounds of restriction enzyme cleavage and adapter ligation produce a set of nested sub-libraries from the initial amplicon library. Sequence reads from these sub-libraries are offset from each other with enough overlap to aid assembly and contig extension. We demonstrate the utility of the long march in resequencing of the Plasmodium falciparum transcriptome, where the number of genomic bases covered was increased by 39%, as well as in metagenomic analysis of a serum sample from a patient with hepatitis B virus (HBV)-related acute liver failure, where the number of HBV bases covered was increased by 42%. We also offer a theoretical optimization of the long march for de novo sequence assembly.

ReCombine: a suite of programs for detection and analysis of meiotic recombination in whole-genome datasets.

In meiosis, the exchange of DNA between chromosomes by homologous recombination is a critical step that ensures proper chromosome segregation and increases genetic diversity. Products of recombination include reciprocal exchanges, known as crossovers, and non-reciprocal gene conversions or non-crossovers. The mechanisms underlying meiotic recombination remain elusive, largely because of the difficulty of analyzing large numbers of recombination events by traditional genetic methods. These traditional methods are increasingly being superseded by high-throughput techniques capable of surveying meiotic recombination on a genome-wide basis. Next-generation sequencing or microarray hybridization is used to genotype thousands of polymorphic markers in the progeny of hybrid yeast strains. New computational tools are needed to perform this genotyping and to find and analyze recombination events. We have developed a suite of programs, ReCombine, for using short sequence reads from next-generation sequencing experiments to genotype yeast meiotic progeny. Upon genotyping, the program CrossOver, a component of ReCombine, then detects recombination products and classifies them into categories based on the features found at each location and their distribution among the various chromatids. CrossOver is also capable of analyzing segregation data from microarray experiments or other sources. This package of programs is designed to allow even researchers without computational expertise to use high-throughput, whole-genome methods to study the molecular mechanisms of meiotic recombination.

An Efficient Method for Identifying Gene Fusions by Targeted RNA Sequencing from Fresh Frozen and FFPE Samples

Fusion genes are known to be key drivers of tumor growth in several types of cancer. Traditionally, detecting fusion genes has been a difficult task based on fluorescent in situ hybridization to detect chromosomal abnormalities. More recently, RNA sequencing has enabled an increased pace of fusion gene identification. However, RNA-Seq is inefficient for the identification of fusion genes due to the high number of sequencing reads needed to detect the small number of fusion transcripts present in cells of interest. Here we describe a method, Single Primer Enrichment Technology (SPET), for targeted RNA sequencing that is customizable to any target genes, is simple to use, and efficiently detects gene fusions. Using SPET to target 5701 exons of 401 known cancer fusion genes for sequencing, we were able to identify known and previously unreported gene fusions from both fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue RNA in both normal tissue and cancer cells.

High Rhodotorula sequences in skin transcriptome of patients with diffuse systemic sclerosis.

Previous studies have suggested a role for pathogens as a trigger of systemic sclerosis (SSc), though neither a pathogen nor a mechanism of pathogenesis is known. Here we show enrichment of Rhodotorula sequences in the skin of patients with early, diffuse SSc compared to normal controls. RNA-seq was performed on four SSc and four controls, to a depth of 200 million reads per patient. Data were analyzed to quantify the non-human sequence reads in each sample. We found little difference between bacterial microbiome and viral read counts, but found a significant difference between the read counts for a mycobiome component, R. glutinis. Normal samples contained almost no detected R. glutinis or other Rhodotorula sequence reads (mean score 0.021 for R. glutinis, 0.024 for all Rhodotorula). In contrast, SSc samples had a mean score of 5.039 for R. glutinis (5.232 for Rhodotorula). We were able to assemble the D1–D2 hypervariable region of the 28S rRNA of R. glutinis from each of the SSc samples. Taken together, these results suggest R. glutinis may be present in the skin of early SSc patients at higher levels than normal skin, raising the possibility that it may be triggering the inflammatory response found in SSc.

IMSA: Integrated Metagenomic Sequence Analysis for Identification of Exogenous Reads in a Host Genomic Background

Metagenomics, the study of microbial genomes within diverse environments, is a rapidly developing field. The identification of microbial sequences within a host organism enables the study of human intestinal, respiratory, and skin microbiota, and has allowed the identification of novel viruses in diseases such as Merkel cell carcinoma. There are few publicly available tools for metagenomic high throughput sequence analysis. We present Integrated Metagenomic Sequence Analysis (IMSA), a flexible, fast, and robust computational analysis pipeline that is available for public use. IMSA takes input sequence from high throughput datasets and uses a user-defined host database to filter out host sequence. IMSA then aligns the filtered reads to a user-defined universal database to characterize exogenous reads within the host background. IMSA assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA also outputs the specific sequence reads assigned to a taxon of interest for downstream analysis. We demonstrate the use of IMSA to detect pathogens and normal flora within sequence data from a primary human cervical cancer carrying HPV16, a primary human cutaneous squamous cell carcinoma carrying HPV 16, the CaSki cell line carrying HPV16, and the HeLa cell line carrying HPV18.

Antiviral gene expression in psoriasis.

Psoriasis patients have relatively infrequent cutaneous viral infections compared to atopic dermatitis patients. Increased expression of four antiviral proteins (MX1, BST2, ISG15 and OAS2) has been reported in psoriatic skin and genetic studies of psoriasis have identified susceptibility genes in antiviral pathways.