3,064 research outputs found
Comparative Gene Expression Profiling of Benign and Malignant Lesions Reveals Candidate Therapeutic Compounds for Leiomyosarcoma
Leiomyosarcoma (LMS) is a malignant, soft-tissue tumor for which few effective therapies exist. Previously, we showed that there are three molecular subtypes of LMS. Here, we analyzed genes differentially expressed in each of the three LMS subtypes as compared to benign leiomyomas and then used the Connectivity Map (cmap) to calculate enrichment scores for the 1309 cmap drugs in order to identify candidate molecules with the potential to induce a benign, leiomyoma-like phenotype in LMS cells. 11 drugs were selected and tested for their ability to inhibit the growth of three human LMS cell lines. We identified two drugs with in vitro efficacy against LMS, one of which had a strongly negative enrichment score (Cantharidin) and the other of which had a strongly positive enrichment score (MG-132). Given MG-132's strong inhibitory effect on LMS cell viability, we hypothesized that LMS cells may be sensitive to treatment with other proteasome inhibitors and demonstrated that bortezomib, a clinically-approved proteasome inhibitor not included in the original cmap screen, potently inhibited the viability of the LMS cell lines. These findings suggest that systematically linking LMS subtype-specific expression signatures with drug-associated expression profiles represents a promising approach for the identification of new drugs for LMS
Importance of collection in gene set enrichment analysis of drug response in cancer cell lines
Gene set enrichment analysis (GSEA) associates gene sets and phenotypes, its use is predicated on the choice of a pre-defined collection of sets. The defacto standard implementation of GSEA provides seven collections yet there are no guidelines for the choice of collections and the impact of such choice, if any, is unknown. Here we compare each of the standard gene set collections in the context of a large dataset of drug response in human cancer cell lines. We define and test a new collection based on gene co-expression in cancer cell lines to compare the performance of the standard collections to an externally derived cell line based collection. The results show that GSEA findings vary significantly depending on the collection chosen for analysis. Henceforth, collections should be carefully selected and reported in studies that leverage GSEA
[S IV] in the NGC 5253 Supernebula: Ionized Gas Kinematics at High Resolution
The nearby dwarf starburst galaxy NGC 5253 hosts a deeply embedded
radio-infrared supernebula excited by thousands of O stars. We have observed
this source in the 10.5{\mu}m line of S+3 at 3.8 kms-1 spectral and 1.4"
spatial resolution, using the high resolution spectrometer TEXES on the IRTF.
The line profile cannot be fit well by a single Gaussian. The best simple fit
describes the gas with two Gaussians, one near the galactic velocity with FWHM
33.6 km s-1 and another of similiar strength and FWHM 94 km s-1 centered \sim20
km s-1 to the blue. This suggests a model for the supernebula in which gas
flows towards us out of the molecular cloud, as in a "blister" or "champagne
flow" or in the HII regions modelled by Zhu (2006).Comment: Accepted for publication in the Astrophysical Journal 4 June 201
A Diverse Array of Cancer-Associated MTOR Mutations Are Hyperactivating and Can Predict Rapamycin Sensitivity
Genes encoding components of the PI3K–AKT–mTOR signaling axis are frequently mutated in cancer, but few mutations have been characterized in MTOR, the gene encoding the mTOR kinase. Using publicly available tumor genome sequencing data, we generated a comprehensive catalog of mTOR pathway mutations in cancer, identifying 33 MTOR mutations that confer pathway hyperactivation. The mutations cluster in six distinct regions in the C-terminal half of mTOR and occur in multiple cancer types, with one cluster particularly prominent in kidney cancer. The activating mutations do not affect mTOR complex assembly, but a subset reduces binding to the mTOR inhibitor DEPTOR. mTOR complex 1 (mTORC1) signaling in cells expressing various activating mutations remains sensitive to pharmacologic mTOR inhibition, but is partially resistant to nutrient deprivation. Finally, cancer cell lines with hyperactivating MTOR mutations display heightened sensitivity to rapamycin both in culture and in vivo xenografts, suggesting that such mutations confer mTOR pathway dependency.
Significance: We report that a diverse set of cancer-associated MTOR mutations confer increased mTORC1/2 pathway activity and that cells harboring these mutations are highly sensitive to rapamycin in culture and in vivo. These findings are clinically relevant as the MTOR mutations characterized herein may serve as biomarkers for predicting tumor responses to mTOR inhibitors.Starr Cancer ConsortiumDavid H. Koch Institute for Integrative Cancer Research at MITAlexander and Margaret Stewart TrustNational Institutes of Health (U.S.) (Grant CA103866)National Institutes of Health (U.S.) (Grant CA129105)National Institutes of Health (U.S.) (Grant AI07389
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Estrogen receptor negative/progesterone receptor positive breast cancer is not a reproducible subtype
Introduction: Estrogen receptor (ER) and progesterone receptor (PR) testing are performed in the evaluation of breast cancer. While the clinical utility of ER as a predictive biomarker to identify patients likely to benefit from hormonal therapy is well-established, the added value of PR is less well-defined. The primary goals of our study were to assess the distribution, inter-assay reproducibility, and prognostic significance of breast cancer subtypes defined by patterns of ER and PR expression. Methods: We integrated gene expression microarray (GEM) and clinico-pathologic data from 20 published studies to determine the frequency (n = 4,111) and inter-assay reproducibility (n = 1,752) of ER/PR subtypes (ER+/PR+, ER+/PR-, ER-/PR-, ER-/PR+). To extend our findings, we utilized a cohort of patients from the Nurses’ Health Study (NHS) with ER/PR data recorded in the medical record and assessed on tissue microarrays (n = 2,011). In both datasets, we assessed the association of ER and PR expression with survival. Results: In a genome-wide analysis, progesterone receptor was among the least variable genes in ER- breast cancer. The ER-/PR+ subtype was rare (approximately 1 to 4%) and showed no significant reproducibility (Kappa = 0.02 and 0.06, in the GEM and NHS datasets, respectively). The vast majority of patients classified as ER-/PR+ in the medical record (97% and 94%, in the GEM and NHS datasets) were re-classified by a second method. In the GEM dataset (n = 2,731), progesterone receptor mRNA expression was associated with prognosis in ER+ breast cancer (adjusted P <0.001), but not in ER- breast cancer (adjusted P = 0.21). PR protein expression did not contribute significant prognostic information to multivariate models considering ER and other standard clinico-pathologic features in the GEM or NHS datasets. Conclusion: ER-/PR+ breast cancer is not a reproducible subtype. PR expression is not associated with prognosis in ER- breast cancer, and PR does not contribute significant independent prognostic information to multivariate models considering ER and other standard clinico-pathologic factors. Given that PR provides no clinically actionable information in ER+ breast cancer, these findings question the utility of routine PR testing in breast cancer
The Effect of Compositional Context on Synthetic Gene Networks
It is well known that synthetic gene expression is highly sensitive to how genetic elements (promoter structure, spacing regions between promoter and coding sequences, ribosome binding sites, etc.) are spatially configured. An important topic that has received far less attention is how the compositional context, or spatial arrangement, of entire genes within a synthetic gene network affects their individual expression levels. In this paper we show, both quantitatively and qualitatively, that compositional context significantly alters transcription levels in synthetic gene networks. We demonstrate that key characteristics of gene induction, such as ultra-sensitivity and dynamic range, strongly depend on compositional context. We postulate that supercoiling can be used to explain this interference and validate this hypothesis through modeling and a series of in vitro supercoiling relaxation experiments. This compositional interference enables a novel form of feedback in synthetic gene networks. We illustrate the use of this feedback by redesigning the toggle switch to incorporate compositional context. We show the context-optimized toggle switch has improved threshold detection and memory properties
SPOP Promotes Ubiquitination and Degradation of the ERG Oncoprotein to Suppress Prostate Cancer Progression
The ERG gene is fused to TMPRSS2 in approximately 50% of prostate cancers (PrCa), resulting in its overexpression. However, whether this is the sole mechanism underlying ERG elevation in PrCa is currently unclear. Here we report that ERG ubiquitination and degradation are governed by the Cullin 3-based ubiquitin ligase SPOP and that deficiency in this pathway leads to aberrant elevation of the ERG oncoprotein. Specifically, we find that truncated ERG (ΔERG), encoded by the ERG fusion gene, is stabilized by evading SPOP-mediated destruction, whereas prostate cancer-associated SPOP mutants are also deficient in promoting ERG ubiquitination. Furthermore, we show that the SPOP/ERG interaction is modulated by CKI-mediated phosphorylation. Importantly, we demonstrate that DNA damage drugs, topoisomerase inhibitors, can trigger CKI activation to restore the SPOP/ΔERG interaction and its consequent degradation. Therefore, SPOP functions as a tumor suppressor to negatively regulate the stability of the ERG oncoprotein in prostate cancer
Digital Quantification of Gene Expression in Sequential Breast Cancer Biopsies Reveals Activation of an Immune Response
Advancements in molecular biology have unveiled multiple breast cancer promoting pathways and potential therapeutic targets. Large randomized clinical trials remain the ultimate means of validating therapeutic efficacy, but they require large cohorts of patients and are lengthy and costly. A useful approach is to conduct a window of opportunity study in which patients are exposed to a drug pre-surgically during the interval between the core needle biopsy and the definitive surgery. These are non-therapeutic studies and the end point is not clinical or pathological response but rather evaluation of molecular changes in the tumor specimens that can predict response. However, since the end points of the non-therapeutic studies are biologic, it is critical to first define the biologic changes that occur in the absence of treatment. In this study, we compared the molecular profiles of breast cancer tumors at the time of the diagnostic biopsy versus the definitive surgery in the absence of any intervention using the Nanostring nCounter platform. We found that while the majority of the transcripts did not vary between the two biopsies, there was evidence of activation of immune related genes in response to the first biopsy and further investigations of the immune changes after a biopsy in early breast cancer seem warranted
Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus
BACKGROUND: Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease. METHODS: We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium(R) HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes. RESULTS: Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy. CONCLUSION: This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy
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