Michael Krauthammer

In Vivo Identification of Tumor- Suppressive PTEN ceRNAs in an Oncogenic BRAF-Induced Mouse Model of Melanoma

Summary We recently proposed that competitive endogenous RNAs (ceRNAs) sequester microRNAs to regulate mRNA transcripts containing common microRNA recognition elements (MREs). However, the functional role of ceRNAs in cancer remains unknown. Loss of PTEN, a tumor suppressor regulated by ceRNA activity, frequently occurs in melanoma. Here, we report the discovery of significant enrichment of putative PTEN ceRNAs among genes whose loss accelerates tumorigenesis following Sleeping Beauty insertional mutagenesis in a mouse model of melanoma. We validated several putative PTEN ceRNAs and further characterized one, the ZEB2 transcript. We show that ZEB2 modulates PTEN protein levels in a microRNA-dependent, protein coding-independent manner. Attenuation of ZEB2 expression activates the PI3K/AKT pathway, enhances cell transformation, and commonly occurs in human melanomas and other cancers expressing low PTEN levels. Our study genetically identifies multiple putative microRNA decoys for PTEN, validates ZEB2 mRNA as a bona fide PTEN ceRNA, and demonstrates that abrogated ZEB2 expression cooperates with BRAF V600E to promote melanomagenesis.We recently proposed that competitive endogenous RNAs (ceRNAs) sequester microRNAs to regulate mRNA transcripts containing common microRNA recognition elements (MREs). However, the functional role of ceRNAs in cancer remains unknown. Loss of PTEN, a tumor suppressor regulated by ceRNA activity, frequently occurs in melanoma. Here, we report the discovery of significant enrichment of putative PTEN ceRNAs among genes whose loss accelerates tumorigenesis following Sleeping Beauty insertional mutagenesis in a mouse model of melanoma. We validated several putative PTEN ceRNAs and further characterized one, the ZEB2 transcript. We show that ZEB2 modulates PTEN protein levels in a microRNA-dependent, protein coding-independent manner. Attenuation of ZEB2 expression activates the PI3K/AKT pathway, enhances cell transformation, and commonly occurs in human melanomas and other cancers expressing low PTEN levels. Our study genetically identifies multiple putative microRNA decoys for PTEN, validates ZEB2 mRNA as a bona fide PTEN ceRNA, and demonstrates that abrogated ZEB2 expression cooperates with BRAF(V600E) to promote melanomagenesis.

PLX4032, a selective BRAFV600E kinase inhibitor, activates the ERK pathway and enhances cell migration and proliferation of BRAFWT melanoma cells

BRAFV600E/K is a frequent mutationally active tumor‐specific kinase in melanomas that is currently targeted for therapy by the specific inhibitor PLX4032. Our studies with melanoma tumor cells that are BRAFV600E/K and BRAFWT showed that, paradoxically, while PLX4032 inhibited ERK1/2 in the highly sensitive BRAFV600E/K, it activated the pathway in the resistant BRAFWT cells, via RAF1 activation, regardless of the status of mutations in NRAS or PTEN. The persistently active ERK1/2 triggered downstream effectors in BRAFWT melanoma cells and induced changes in the expression of a wide‐spectrum of genes associated with cell cycle control. Furthermore, PLX4032 increased the rate of proliferation of growth factor‐dependent NRAS Q61L mutant primary melanoma cells, reduced cell adherence and increased mobility of cells from advanced lesions. The results suggest that the drug can confer an advantage to BRAFWT primary and metastatic tumor cells in vivo and provide markers for monitoring clinical responses.

Term identification in the biomedical literature

Sophisticated information technologies are needed for effective data acquisition and integration from a growing body of the biomedical literature. Successful term identification is key to getting access to the stored literature information, as it is the terms (and their relationships) that convey knowledge across scientific articles. Due to the complexities of a dynamically changing biomedical terminology, term identification has been recognized as the current bottleneck in text mining, and--as a consequence--has become an important research topic both in natural language processing and biomedical communities. This article overviews state-of-the-art approaches in term identification. The process of identifying terms is analysed through three steps: term recognition, term classification, and term mapping. For each step, main approaches and general trends, along with the major problems, are discussed. By assessing previous work in context of the overall term identification process, the review also tries to delineate needs for future work in the field.

GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data

The immense growth in the volume of research literature and experimental data in the field of molecular biology calls for efficient automatic methods to capture and store information. In recent years, several groups have worked on specific problems in this area, such as automated selection of articles pertinent to molecular biology, or automated extraction of information using natural-language processing, information visualization, and generation of specialized knowledge bases for molecular biology. GeneWays is an integrated system that combines several such subtasks. It analyzes interactions between molecular substances, drawing on multiple sources of information to infer a consensus view of molecular networks. GeneWays is designed as an open platform, allowing researchers to query, review, and critique stored information.

Using BLAST for identifying gene and protein names in journal articles

We describe a system which automatically identifies gene and protein names in journal articles, an important and non-trivial first step in knowledge extraction of protein and gene actions. Our system uses a database of gene and protein names and is based on BLAST [Altschul et al., Nucleic Acids Res. 25 (1997) 3389-3402], a popular tool for DNA and protein sequence comparison. We describe a method that consists of mapping sequences of text characters into sequences of nucleotides that can be processed by BLAST. We demonstrate that this approach is feasible: the system matches gene and protein names with a recall of 78.8% and a precision of 71.7%, which includes names that are not part of the system database. An analysis of the results suggests techniques that can be used to improve performance further.

Genome-wide screen of promoter methylation identifies novel markers in melanoma

DNA methylation is an important component of epigenetic modifications, which influences the transcriptional machinery aberrant in many human diseases. In this study we present the first genome-wide integrative analysis of promoter methylation and gene expression for the identification of methylation markers in melanoma. Genome-wide promoter methylation and gene expression of eight early-passage human melanoma cell strains were compared with newborn and adult melanocytes. We used linear mixed effect models (LME) in combination with a series of filters based on the localization of promoter methylation relative to the transcription start site, overall promoter CpG content, and differential gene expression to discover DNA methylation markers. This approach identified 76 markers, of which 68 were hyper- and eight hypomethylated (LME, P < 0.05). Promoter methylation and differential gene expression of five markers (COL1A2, NPM2, HSPB6, DDIT4L, MT1G) were validated by sequencing of bisulfite-modified DNA and real-time reverse transcriptase PCR, respectively. Importantly, the incidence of promoter methylation of the validated markers increased moderately in early and significantly in advanced-stage melanomas, using early-passage cell strains and snap-frozen tissues (n = 18 and n = 24, respectively) compared with normal melanocytes and nevi (n = 11 and n = 9, respectively). Our approach allows robust identification of methylation markers that can be applied to other studies involving genome-wide promoter methylation. In conclusion, this study represents the first unbiased systematic effort to determine methylation markers in melanoma and revealed several novel genes regulated by promoter methylation that were not described in cancer cells before.

Exome sequencing identifies recurrent mutations in NF1 and RASopathy genes in sun-exposed melanomas

We report on whole-exome sequencing (WES) of 213 melanomas. Our analysis established NF1, encoding a negative regulator of RAS, as the third most frequently mutated gene in melanoma, after BRAF and NRAS. Inactivating NF1 mutations were present in 46% of melanomas expressing wild-type BRAF and RAS, occurred in older patients and showed a distinct pattern of co-mutation with other RASopathy genes, particularly RASA2. Functional studies showed that NF1 suppression led to increased RAS activation in most, but not all, melanoma cases. In addition, loss of NF1 did not predict sensitivity to MEK or ERK inhibitors. The rebound pathway, as seen by the induction of phosphorylated MEK, occurred in cells both sensitive and resistant to the studied drugs. We conclude that NF1 is a key tumor suppressor lost in melanomas, and that concurrent RASopathy gene mutations may enhance its role in melanomagenesis.

Yale Image Finder (YIF)

UNLABELLED Yale Image Finder (YIF) is a publicly accessible search engine featuring a new way of retrieving biomedical images and associated papers based on the text carried inside the images. Image queries can also be issued against the image caption, as well as words in the associated paper abstract and title. A typical search scenario using YIF is as follows: a user provides few search keywords and the most relevant images are returned and presented in the form of thumbnails. Users can click on the image of interest to retrieve the high resolution image. In addition, the search engine will provide two types of related images: those that appear in the same paper, and those from other papers with similar image content. Retrieved images link back to their source papers, allowing users to find related papers starting with an image of interest. Currently, YIF has indexed over 140 000 images from over 34 000 open access biomedical journal papers. AVAILABILITY http://krauthammerlab.med.yale.edu/imagefinder/

Melanoma Prognostic Model Using Tissue Microarrays and Genetic Algorithms

PURPOSE As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence. METHODS Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004. RESULTS Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than -0.052, p21(WAF1) nuclear compartment AQUA score of more than 12.98, p16(INK4A) ln(non-nuclear/nuclear AQUA score ratio) of < or = -0.083, beta-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of < or = 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts. CONCLUSION This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.

MicroRNA signatures differentiate melanoma subtypes

Melanoma is an aggressive cancer that is highly resistance to therapies once metastasized. We studied microRNA (miRNA) expression in clinical melanoma subtypes and evaluated different miRNA signatures in the background of gain of function somatic and inherited mutations associated with melanoma. Total RNA from 42 patient derived primary melanoma cell lines and three independent normal primary melanocyte cell cultures was evaluated by miRNA array. MiRNA expression was then analyzed comparing subtypes and additional clinicopathologic criteria including somatic mutations. The prevalence and association of an inherited variant in a miRNA binding site in the 3’UTR of the KRAS oncogene, referred to as the KRAS-variant, was also evaluated. We show that seven miRNAs, miR-142-3p, miR-486, miR-214, miR-218, miR-362, miR-650 and miR-31, were significantly correlated with acral as compared to non-acral melanomas (p < 0.04). In addition, we discovered that the KRAS-variant was enriched in non-acral melanoma (25%), and that miR-137 under expression was significantly associated with melanomas with the KRAS-variant. Our findings indicate that miRNAs are differentially expressed in melanoma subtypes and that their misregulation can be impacted by inherited gene variants, supporting the hypothesis that miRNA misregulation reflects biological differences in melanoma.