Use Of Transcriptional Profiling Research Articles

A Multicenter, Longitudinal Maternal and Birth Cohort Study in Latin America to Assess Prevalent Respiratory Tract Infections in Children from 0 to 5 Years of Age. The MINERVAL Study

Abstract Background A maternal and birth cohort study can assess the etiology and clinical course of lower respiratory tract infections and offers the opportunity to evaluate the relationship between sociodemographic, clinical, host characteristics and disease severity. In Latin America, a consortium of clinical research centers in Colombia and Panama has demonstrated its ability to conduct long-term longitudinal studies involving active surveillance of thousands of children with consistent retention rates. The MINERVAL cohort study aims to estimate the incidence, etiology, severity, and burden of lower respiratory tract infections (LRTI) and to identify microbiome and transcriptome profiles to help predict risk and assess disease severity in children from birth to 5 years of age. Methods We are establishing a maternal/birth cohort study in four sites (Cali, Bogota, Barranquilla and Panama), and will be recruiting 542 participants per center. Enrolled pregnant women between 24 and 27 weeks of gestation, and newborns under 4 weeks of age, will be closely followed with active surveillance weekly during the first 2 years for early detection of LRTI. Monthly telephone follow-up calls will continue until five years of age to assess the development of long-term respiratory morbidity and complications, including recurrent wheezing episodes. Clinical samples (NP swabs -for respiratory pathogen detection and microbiome analysis-, and blood -for cytokine and transcriptome analysis-) will be obtained in pregnant women, and in infants in the first 4 weeks of life and every 6 months for two years. Women and children who develop LRTI during the longitudinal follow-up will be evaluated clinically and samples will be collected. Results This cohort will provide prospective data and biological samples at crucial stages of children’s development, to allow estimation of the incidence and burden of LRTI by age and etiology, and the identification of risk factors and possible targets for intervention. Furthermore, the use of transcriptional profiling will allow early identification of variables to predict and guide clinical management in children, the use of antivirals and monoclonal antibodies, and to prioritize the population to be vaccinated according to age and risk factors. Conclusion The establishment of observational maternal and birth cohorts in Latin America could provide information to guide the development of strategies to prevent and mitigate the impact of respiratory tract infections in young children. Collaboration among investigators in the region and partnerships with international investigators optimizes resources and allows standardization of good surveillance practices, data exchange and the generation of new knowledge for future studies.

Transcriptome-guided metabolic network analysis reveals rearrangements of carbon flux distribution in Neisseria gonorrhoeae during neutrophil co-culture.

The ability of bacterial pathogens to metabolically adapt to the environmental conditions of their hosts is critical to both colonization and invasive disease. Infection with Neisseria gonorrhoeae (the gonococcus, Gc) is characterized by the influx of neutrophils [polymorphonuclear leukocytes (PMNs)], which fail to clear the bacteria and make antimicrobial products that can exacerbate tissue damage. The inability of the human host to clear Gc infection is particularly concerning in light of the emergence of strains that are resistant to all clinically recommended antibiotics. Bacterial metabolism represents a promising target for the development of new therapeutics against Gc. Here, we generated a curated genome-scale metabolic network reconstruction (GENRE) of Gc strain FA1090. This GENRE links genetic information to metabolic phenotypes and predicts Gc biomass synthesis and energy consumption. We validated this model with published data and in new results reported here. Contextualization of this model using the transcriptional profile of Gc exposed to PMNs revealed substantial rearrangements of Gc central metabolism and induction of Gc nutrient acquisition strategies for alternate carbon source use. These features enhanced the growth of Gc in the presence of neutrophils. From these results, we conclude that the metabolic interplay between Gc and PMNs helps define infection outcomes. The use of transcriptional profiling and metabolic modeling to reveal new mechanisms by which Gc persists in the presence of PMNs uncovers unique aspects of metabolism in this fastidious bacterium, which could be targeted to block infection and thereby reduce the burden of gonorrhea in the human population. IMPORTANCE The World Health Organization designated Gc as a high-priority pathogen for research and development of new antimicrobials. Bacterial metabolism is a promising target for new antimicrobials, as metabolic enzymes are widely conserved among bacterial strains and are critical for nutrient acquisition and survival within the human host. Here we used genome-scale metabolic modeling to characterize the core metabolic pathways of this fastidious bacterium and to uncover the pathways used by Gc during culture with primary human immune cells. These analyses revealed that Gc relies on different metabolic pathways during co-culture with human neutrophils than in rich media. Conditionally essential genes emerging from these analyses were validated experimentally. These results show that metabolic adaptation in the context of innate immunity is important to Gc pathogenesis. Identifying the metabolic pathways used by Gc during infection can highlight new therapeutic targets for drug-resistant gonorrhea.

Hidden Gems in the Transcriptome Maps of Competent Streptococci.

Natural transformation is regarded as an important mechanism in bacteria that allows for adaptation to different environmental stressors by ensuring genome plasticity. Since the discovery of this phenomenon in Streptococcus pneumoniae, remarkable progress has been made in the understanding of the molecular mechanisms and pathways coordinating this process. Recently, the advent of high-throughput sequencing allows the posing of questions that address the system at a larger scale but also allow for the creation of high-resolution maps of transcription. Thus, while much is already known about genetic competence in streptococci, recent studies continue to reveal intricate novel regulation pathways and components. In this perspective article, we highlight the use of transcriptional profiling and mapping as a valuable resource in the identification and characterization of “hidden gems” pertinent to the natural transformation system. Such strategies have recently been employed in a variety of different species. In S. mutans, for example, genome editing combined with the power of promoter mapping and RNA-Seq allowed for the identification of a link between the ComCDE and the ComRS systems, a ComR positive feedback loop mediated by SigX, and the XrpA peptide, encoded within sigX, which inhibits competence. In S. pneumoniae, a novel member of the competence regulon termed BriC was found to be directly under control of ComE and to promote biofilm formation and nasopharyngeal colonization but not competence. Together these new technologies enable us to discover new links and to revisit old pathways in the compelling study of natural genetic transformation.

Advances in understanding – genetic basis of intellectual disability

Intellectual disability is the most common developmental disorder characterized by a congenital limitation in intellectual functioning and adaptive behavior. It often co-occurs with other mental conditions like attention deficit/hyperactivity disorder and autism spectrum disorder, and can be part of a malformation syndrome that affects other organs. Considering the heterogeneity of its causes (environmental and genetic), its frequency worldwide varies greatly. This review focuses on known genes underlying (syndromic and non-syndromic) intellectual disability, it provides a succinct analysis of their Gene Ontology, and it suggests the use of transcriptional profiling for the prioritization of candidate genes.

Toxicogenomic assessment of liver responses following subchronic exposure to furan in Fischer F344 rats.

Furan is a widely used industrial chemical and a contaminant in heated foods. Chronic furan exposure causes cholangiocarcinoma and hepatocellular tumors in rats at doses of 2 mg/kg bw/day or greater, with gender differences in frequency and severity. The hepatic transcriptional alterations induced by low doses of furan (doses below those previously tested for induction of liver tumors) and the potential mechanisms underlying gender differences are largely unexplored. We used DNA microarrays to examine the global hepatic mRNA and microRNA transcriptional profiles of male and female rats exposed to 0, 0.03, 0.12, 0.5 or 2 mg/kg bw/day furan over 90 days. Marked gender differences in gene expression responses to furan were observed, with many more altered genes in exposed males than females, confirming the increased sensitivity of males even at the low doses. Pathway analysis supported that key events in furan-induced liver tumors in males include gene expression changes related to oxidative stress, apoptosis and inflammatory response, while pathway changes in females were consistent with primarily adaptive responses. Pathway benchmark doses (BMDs) were estimated and compared to relevant apical endpoints. Transcriptional pathway BMDs could only be examined in males. These median BMDs ranged from 0.08 to 1.43 mg/kg bw/day and approximated those derived from traditional histopathology. MiR-34a (a P53 target) was the only microRNA significantly increased at the 2 mg/kg bw/day, providing evidence to support the importance of apoptosis and cell proliferation in furan hepatotoxicity. Overall, this study demonstrates the use of transcriptional profiling to discern mode of action and mechanisms involved in gender differences.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-015-1561-2) contains supplementary material, which is available to authorized users.

Expanding fundamental ecological knowledge by studying urban ecosystems

The expansion, densification and proliferation of urban areas around the world is currently occurring at a rate that is unprecedented in human history. It is predicted that global urban land cover will triple between 2000 and 2030, with some regions (including biodiversity hotspots) experiencing a ninefold increase in urban land cover over the same time period (Seto, G€ uneralp & Hutyra 2012). Accompanying the expansion of urban landscapes, it is anticipated that the human population living in cities and towns globally will increase from 3 5 to 5 billion people within the next 20 years (Fragkias et al. 2013). Thus, the demands of an expanding and urbanizing human population are one of the pressing ecological problems our world is facing (Sanderson et al. 2002), alongside, and in combination with, global climate change and changes to biodiversity at local and global scales (Pimm et al. 2014). Yet, urban environments also present a unique opportunity to expand our fundamental knowledge related to ecology and evolution due to the presence of intense and often novel selection pressures. In the inaugural issue of this journal, Calow (1987) defined functional ecology as the sum of three interactive processes: (i) those occurring between organisms and their environment, (ii) biotic interactions between organisms and (iii) adaptive processes driven by natural selection. The same three processes were highlighted 1 year earlier by Jared Diamond in Nature, when he called for biologists to pay more attention to the potential of using the unprecedented environmental conditions that exist within towns and cities to develop and test evolutionary and ecological theory (Diamond 1986). There is thus a natural synergy between functional ecology and urban ecology, as exemplified by some of the classic papers that have appeared in this journal, such as Rydell (1992) who demonstrated that the form of echolocation system determined the impact of light pollution on bat foraging behaviour. The potential of combining functional ecological research with urban ecology is, however, a long way from being fully realized. This is in part explained by the youth of urban ecology as a discipline. Scientific enquiry into the ecological consequences of urban environments has been underway for over half a century, although most of the momentum emerged after the mid 1990s (McDonnell 2011; Wu 2014). Thus, the focus of much urban research to date has involved describing patterns along environmental gradients (Gagn e 2013; McDonnell & Hahs 2013) rather than investigating the mechanistic processes that lie at the heart of functional ecology. To be effective in addressing the global challenges of urbanization, a much better understanding of how the urban environment affects the ecology and evolution of organisms needs to be developed (Grimm et al. 2008; Marzluff 2012; Gil & Brumm 2014; McDonnell & Hahs 2015). The purpose of this special feature is to draw attention to the plethora of opportunities that await researchers investigating the ecology and evolution of organisms in urban environments. The combination of environmental stressors and conditions within urban areas provides a novel opportunity to test and expand our theories related to ecology and evolution of organisms, and some intriguing insights are already beginning to emerge. For example, the detailed understanding of the molecular, genetic and developmental mechanisms of beak evolution that has arisen from studying Galapagos finches has been significantly advanced by studying beak evolution in the house finch Carpodacus mexicanus in response to novel urban food sources and its consequences for acoustic communication (Badyaev 2010, 2014). Thus, urban ecology has the potential to extend our understanding of extremely well-studied ecological and evolutionary problems.

The Use of Transcriptional Profiling to Improve Personalized Diagnosis and Management of Cutaneous T-cell Lymphoma (CTCL).

Although many patients with mycosis fungoides presenting with stage I disease enjoy an indolent disease course and normal life expectancy, about 15% to 20% of them progress to higher stages and most ultimately succumb to their disease. Currently, it is not possible to predict which patients will progress and which patients will have a stable disease. Previously, we conducted microarray analyses with RT-PCR validation of gene expression in biopsy specimens from 60 patients with stage I-IV cutaneous T-cell lymphoma (CTCL), identified three distinct clusters based upon transcription profile, and correlated our molecular findings with 6 years of clinical follow-up. We test by RT-PCR within our prediction model the expression of about 240 genes that were previously reported to play an important role in CTCL carcinogenesis. We further extend the clinical follow-up of our patients to 11 years. We compare the expression of selected genes between mycosis fungoides/Sézary syndrome and benign inflammatory dermatoses that often mimic this cancer. Our findings demonstrate that 52 of the about 240 genes can be classified into cluster 1-3 expression patterns and such expression is consistent with their suggested biologic roles. Moreover, we determined that 17 genes (CCL18, CCL26, FYB, T3JAM, MMP12, LEF1, LCK, ITK, GNLY, IL2RA, IL26, IL22, CCR4, GTSF1, SYCP1, STAT5A, and TOX) are able to both identify patients who are at risk of progression and also distinguish mycosis fungoides/Sézary syndrome from benign mimickers. This study, combined with other gene expression analyses, prepares the foundation for the development of personalized molecular approach toward diagnosis and treatment of CTCL.

Research highlights for issue 2: recent applications in molecular evolution.

Research highlights for issue 2: recent applications in molecular evolution.

Use of Transcriptional Profiling to Delineate the Initial Response of Mice to Intravaginal Herpes Simplex Virus Type 2 Infection

Intravaginal (ivag) infection of mice with herpes simplex virus type 2 (HSV-2) causes genital tissue damage, quickly followed by development of fatal encephalopathy. To delineate initial host responses generated by HSV-2 infection, here oligonucleotide microarrays compared gene expression in vaginal tissue from uninfected mice and mice 1, 2, 3, 4, 5, 6, or 7 days after ivag infection with 10(4) pfu HSV-2. While comparison of mRNA expression in uninfected and HSV-infected vaginal tissue detected few changes during the first 2 days post infection (dpi), there were 156 genes whose expression was first significantly altered 3 dpi that remained significantly modified at all later time points examined. These 156 genes were significantly enriched in canonical pathways associated with interferon (IFN) signaling, activation of IFN elements by intracellular pattern recognition receptors, and antiviral immunity induced by cytosolic RIG-like receptors. Evaluation of this gene set with the National Center for Biotechnology Information Gene and INTERFEROME databases corroborated pathway analysis, as function of most (53%) were linked to IFN-mediated host immunity. In the final set of experiments, ivag administration of the Toll-like receptor 3 agonist polyinosinic: polycytidylic acid (poly I:C) 24 h before ivag HSV-2 infection reduced the incidence of genital pathology and encephalopathy, while these poly I:C-treated mice were subsequently protected from ocular HSV-2 challenge lethal to uninfected controls. The latter results imply that the exuberant antiviral immunity produced in our experimental model is simply formed too late to prevent viral replication and dissemination, and that poly I:C-induced formation of an antiviral state protecting against primary ivag infection also permits development of HSV-specific protective immunity.

Determination of minimal transcriptional signatures of compounds for target prediction

The identification of molecular target and mechanism of action of compounds is a key hurdle in drug discovery. Multiplexed techniques for bead-based expression profiling allow the measurement of transcriptional signatures of compound-treated cells in high-throughput mode. Such profiles can be used to gain insight into compounds' mode of action and the protein targets they are modulating. Through the proxy of target prediction from such gene signatures we explored important aspects of the use of transcriptional profiles to capture biological variability of perturbed cellular assays. We found that signatures derived from expression data and signatures derived from biological interaction networks performed equally well, and we showed that gene signatures can be optimised using a genetic algorithm. Gene signatures of approximately 128 genes seemed to be most generic, capturing a maximum of the perturbation inflicted on cells through compound treatment. Moreover, we found evidence for oxidative phosphorylation to be one of the most general ways to capture compound perturbation.

Modulation of fungal sensitivity to staurosporine by targeting proteins identified by transcriptional profiling

An analysis of the time-dependent genetic response to the death-inducer staurosporine was performed in Neurospora crassa by transcriptional profiling. Staurosporine induced two major genes encoding an ABC transporter and a protein with similarity to regulatory subunits of potassium channels. The transcriptional response is dependent on the activity of a novel transcription factor. Deletion mutants in differentially expressed genes displayed altered sensitivity to staurosporine, underscoring significant proteins involved in the response to the drug. A null-mutant of the ABC transporter (abc3) is extremely sensitive to staurosporine, accumulates more staurosporine than the wild type strain and is defective in energy-dependent export of the drug, indicating that the ABC3 protein is the first described staurosporine transporter. It was located in the plasma membrane by immunofluorescence microscopy. The combination of inhibitors of ABC transporters or of potassium channels with staurosporine leads to an enhanced activity against N. crassa and pathogenic fungi paving the way to the development of more potent and specific antifungals. Our results highlight the general use of transcriptional profiling for the identification of novel proteins involved in cell death and their potential use as drug targets.

Minimization of immunosuppression in adult liver transplantation: new strategies and tools

To describe most relevant data regarding strategies to achieve immunosuppression minimization and/or complete withdrawal in liver transplantation and to discuss the development of tolerance biomarkers to predict the success of immunosuppression weaning. In clinical organ transplantation allograft tolerance has been attained through two different pathways: (1) tolerance or immunosuppression minimization has been attempted by administering induction therapies with or without infusion of donor hematopoietic cells; and (2) the availability of spontaneously tolerant liver and kidney recipients has been exploited to develop biomarkers of allograft tolerance. The use of transcriptional profiling is the most promising approach. Recent publications have identified a gene expression signature in tolerant patients. Current immunosuppressive regimens reduce acute rejection episodes but promote a number of complications that have a negative impact on patient morbidity, mortality and quality of life. In this setting, achievement of tolerance is a major goal. Although there are no reliable markers to identify tolerant patients, recent studies have found that tolerant liver recipients exhibit unique peripheral blood transcriptional patterns. The difference in expression patterns is related to the immune response and could constitute the basis of a future diagnostic test of tolerance.

Sequential Use of Transcriptional Profiling, Expression Quantitative Trait Mapping, and Gene Association Implicates MMP20 in Human Kidney Aging

Kidneys age at different rates, such that some people show little or no effects of aging whereas others show rapid functional decline. We sequentially used transcriptional profiling and expression quantitative trait loci (eQTL) mapping to narrow down which genes to test for association with kidney aging. We first performed whole-genome transcriptional profiling to find 630 genes that change expression with age in the kidney. Using two methods to detect eQTLs, we found 101 of these age-regulated genes contain expression-associated SNPs. We tested the eQTLs for association with kidney aging, measured by glomerular filtration rate (GFR) using combined data from the Baltimore Longitudinal Study of Aging (BLSA) and the InCHIANTI study. We found a SNP association (rs1711437 in MMP20) with kidney aging (uncorrected p = 3.6×10−5, empirical p = 0.01) that explains 1%–2% of the variance in GFR among individuals. The results of this sequential analysis may provide the first evidence for a gene association with kidney aging in humans.

Unwrapping the Laccaria genome

Unwrapping the <i>Laccaria</i> genome

Combining transcriptional profiling and genetic linkage analysis to uncover gene networks operating in hematopoietic stem cells and their progeny

Stem cells are unique in that they possess both the capacity to self-renew and thereby maintain their original pool as well as the capacity to differentiate into mature cells. In the past number of years, transcriptional profiling of enriched stem cell populations has been extensively performed in an attempt to identify a universal stem cell gene expression signature. While stem-cell-specific transcripts were identified in each case, this approach has thus far been insufficient to identify a universal group of core “stemness” genes ultimately responsible for self-renewal and multipotency. Similarly, in the hematopoietic system, comparisons of transcriptional profiles between different hematopoietic cell stages have had limited success in revealing core genes ultimately responsible for the initiation of differentiation and lineage specification. Here, we propose that the combined use of transcriptional profiling and genetic linkage analysis, an approach called “genetical genomics”, can be a valuable tool to assist in the identification of genes and gene networks that specify “stemness” and cell fate decisions. We review past studies of hematopoietic cells that utilized transcriptional profiling and/or genetic linkage analysis, and discuss several potential future applications of genetical genomics.

Adipose Fibroblast Growth Factor 21 Is Up-Regulated by Peroxisome Proliferator-Activated Receptor γ and Altered Metabolic States

Adipose tissue is a metabolically responsive endocrine organ that secretes a myriad of adipokines. Antidiabetic drugs such as peroxisome proliferator-activated receptor (PPAR) gamma agonists target adipose tissue gene expression and correct hyperglycemia via whole-body insulin sensitization. The mechanism by which altered gene expression in adipose tissue affects liver and muscle insulin sensitivity (and thus glucose homeostasis) is not fully understood. One possible mechanism involves the alteration in adipokine secretion, in particular the up-regulation of secreted factors that increase whole-body insulin sensitivity. Here, we report the use of transcriptional profiling to identify genes encoding for secreted proteins the expression of which is regulated by PPARgamma agonists. Of the 379 genes robustly regulated by two structurally distinct PPARgamma agonists in the epididymal white adipose tissue (EWAT) of db/db mice, 33 encoded for known secreted proteins, one of which was FGF21. Although FGF21 was recently reported to be up-regulated in cultured adipocytes by PPARgamma agonists and in liver by PPARalpha agonists and induction of ketotic states, we demonstrate that the protein is transcriptionally up-regulated in adipose tissue in vivo by PPARgamma agonist treatment and under a variety of physiological conditions, including fasting and high fat diet feeding. In addition, we found that circulating levels of FGF21 protein were increased upon treatment with PPARgamma agonists and under ketogenic states. These results suggest a role for FGF21 in mediating the antidiabetic activities of PPARgamma agonists.

Comparing Genetically Engineered Mouse Mammary Cancer Models with Human Breast Cancer by Expression Profiling1

Breast cancer is a heterogeneous disease, and much of the molecular basis for this heterogeneity is being unraveled using advanced genomic technologies. More recently, global transcriptional profiling has proven to be an effective new tool for characterizing human tumors. Genomic "signatures'' have been developed that classify tumors with varying prognoses and responses to treatment. Recent studies have begun to extend the use of global transcriptional profiling to better characterize genetically engineered mouse (GEM) models of breast cancer, which will improve the ability to translate basic research advances into clinical advances. GEM models of mammary carcinoma have proven to be invaluable tools to gain insight into mechanisms underlying tumor initiation, progression, and therapeutic responses in an in vivo system where tumors spontaneously develop in an appropriate tissue environment. This review will discuss the use of transcriptional profiling of breast cancer in tumors from both human patients and GEM models to improve prognostic measures, examine mechanisms of tumor initiation and progression, identify novel therapeutic targets, and improve pre-clinical testing for drug development. Together, these advances offer a framework for classifying human tumors, identifying appropriate GEM models for specific experimental purposes, and utilizing the combined data to identify more specific and effective cancer therapies.

Predicting the age of mosquitoes using transcriptional profiles

The use of transcriptional profiles for predicting mosquito age is a novel solution for the longstanding problem of determining the age of field-caught mosquitoes. Female mosquito age is of central importance to the transmission of a range of human pathogens. The transcriptional age-grading protocol we present here was developed in Aedes aegypti, principally as a research tool. Age predictions are made on the basis of transcriptional data collected from mosquitoes of known age. The abundance of eight candidate gene transcripts is quantified relative to a reference gene using quantitative reverse transcriptase-PCR (RT-PCR). Normalized gene expression (GE) measures are analyzed using canonical redundancy analysis to obtain a multivariate predictor of mosquito age. The relationship between the first redundancy variate and known age is used as the calibration model. Normalized GE measures are quantified for wild-caught mosquitoes, and ages are then predicted using this calibration model. Rearing of mosquitoes to specific ages for calibration data can take up to 40 d. Molecular analysis of transcript abundance, and subsequent age predictions, should take approximately 3-5 d for 100 individuals.

The use of transcriptional profiles to predict adult mosquito age under field conditions.

Age is a critical determinant of an adult female mosquito's ability to transmit a range of human pathogens. Despite its central importance, relatively few methods exist with which to accurately determine chronological age of field-caught mosquitoes. This fact is a major constraint on our ability to fully understand the relative importance of vector longevity to disease transmission in different ecological contexts. It also limits our ability to evaluate novel disease control strategies that specifically target mosquito longevity. We report the development of a transcriptional profiling approach to determine age of adult female Aedes aegypti under field conditions. We demonstrate that this approach surpasses current cuticular hydrocarbon methods for both accuracy of predicted age as well as the upper limits at which age can be reliably predicted. The method is based on genes that display age-dependent expression in a range of dipteran insects and, as such, is likely to be broadly applicable to other disease vectors.

Identification of ADAM10 as a major source of HER2 ectodomain sheddase activity in HER2 overexpressing breast cancer cells

ALL AUTHORS: Phillip C.C. Liu, Xiangdong Liu, Yanlong Li, Maryanne Covington, Richard Wynn, Reid Huber, Milton Hillman, Gengjie Yang, Dawn Ellis, Cindy Marando, Kamna Katiyar, Jodi Bradley, Kenneth Abremski, Mark Stow, Mark Rupar, Jincong Zhuo, Yun-Long Li, Qiyan Lin, David Burns, Meizhong Xu, Colin Zhang, Ding-Quan Qian, Chunhong He, Vaqar Sharief, Lingkai Weng, Costas Agrios, Eric Shi, Brian Metcalf, Robert Newton, Steven Friedman, Wenqing Yaol, Peggy Scherlel, Gregory Hollis, Timothy C. Burn Overexpression and activating mutations of ErbB family members have been implicated in the development and progression of a variety of tumor types. Cleavage of the HER2 receptor by an as yet unidentified ectodomain sheddase has been shown to liberate the HER2 extracellular domain (ECD) leaving a fragment with constitutive kinase activity that can provide ligand-independent growth and survival signals to the cell. This process is clinically relevant since HER2 ECD serum levels in metastatic breast cancer patients are associated with a poorer prognosis. Thus, inhibition of the HER2 sheddase may provide a novel therapeutic approach for breast cancer. We describe the use of transcriptional profiling, pharmacological and in vitro approaches to identify the major source of HER2 sheddase activity. Real-time PCR was used to identify those ADAM family members which were expressed in HER2 shedding cell lines. siRNAs that selectively inhibited ADAM10 expression reduced HER2 shedding. In addition, we profiled over 1000 small molecules for in vitro inhibition of a panel of ADAM and MMP proteins; a positive correlation was observed only between ADAM10 inhibition and reduction of HER2 ECD shedding in a cell based assay. Finally, in vitro studies demonstrate that in combination with low doses of Herceptin, selective ADAM10 inhibitors decrease proliferation in HER2 overexpressing cell lines while inhibitors, that do not inhibit ADAM10, have no impact. These results are consistent with ADAM10 being a major determinant of HER2 shedding, the inhibition of which, may provide a novel therapeutic approach for treating a variety of cancers with active HER2 signaling.