| 1. |
- Jörnsten, Rebecka, 1971, et al.
(författare)
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Network modeling of the transcriptional effects of copy number aberrations in glioblastoma
- 2011
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- DNA copy number aberrations (CNAs) are a hallmark of cancer genomes. However, little is known about how such changes affect global gene expression. We develop a modeling framework, EPoC (Endogenous Perturbation analysis of Cancer), to (1) detect disease-driving CNAs and their effect on target mRNA expression, and to (2) stratify cancer patients into long- and short-term survivors. Our method constructs causal network models of gene expression by combining genome-wide DNA- and RNA-level data. Prognostic scores are obtained from a singular value decomposition of the networks. By applying EPoC to glioblastoma data from The Cancer Genome Atlas consortium, we demonstrate that the resulting network models contain known disease-relevant hub genes, reveal interesting candidate hubs, and uncover predictors of patient survival. Targeted validations in four glioblastoma cell lines support selected predictions, and implicate the p53-interacting protein Necdin in suppressing glioblastoma cell growth. We conclude that large-scale network modeling of the effects of CNAs on gene expression may provide insights into the biology of human cancer. Free software in MATLAB and R is provided.
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| 2. |
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| 3. |
- Petit, Marleen MR, et al.
(författare)
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Smooth muscle expression of lipoma preferred partner is mediated by an alternative intronic promoter that is regulated by serum response factor/myocardin.
- 2008
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Ingår i: Circulation research. - 1524-4571. ; 103:1, s. 61-9
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Tidskriftsartikel (refereegranskat)abstract
- Lipoma preferred partner (LPP) was recently recognized as a smooth muscle marker that plays a role in smooth muscle cell migration. In this report, we focus on the transcriptional regulation of the LPP gene. In particular, we investigate whether LPP is directly regulated by serum response factor (SRF). We show that the LPP gene contains 3 evolutionarily conserved CArG boxes and that 1 of these is part of an alternative promoter in intron 2. Quantitative RT-PCR shows that this alternative promoter directs transcription specifically to smooth muscle containing tissues in vivo. By using chromatin immunoprecipitation, we demonstrate that 2 of the CArG boxes, including the promoter-associated CArG box, bind to endogenous SRF in cultured aortic smooth muscle cells. Electrophoretic mobility-shift assays show that the conserved CArG boxes bind SRF in vitro. In reporter experiments, we show that the alternative promoter has transcriptional capacity that is dependent on SRF/myocardin and that the promoter associated CArG box is required for that activity. Finally, we show by quantitative RT-PCR that the alternative promoter is strongly downregulated in SRF-deficient embryonic stem cells and in smooth muscle tissues derived from conditional SRF knockout mice. Collectively, our data demonstrate that expression of LPP in smooth muscle is mediated by an alternative promoter that is regulated by SRF/myocardin.
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| 4. |
- Weinstein, John N., et al.
(författare)
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The cancer genome atlas pan-cancer analysis project
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:10, s. 1113-1120
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Forskningsöversikt (refereegranskat)abstract
- The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. © 2013 Nature America, Inc. All rights reserved.
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| 5. |
- Abenius, Tobias, 1979, et al.
(författare)
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System-scale network modeling of cancer using EPoC
- 2012
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Ingår i: Advances in Experimental Medicine and Biology. - New York, NY : Springer New York. - 0065-2598. - 9781441972095 ; 736:5, s. 617-643
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Tidskriftsartikel (refereegranskat)abstract
- One of the central problems of cancer systems biology is to understand the complex molecular changes of cancerous cells and tissues, and use this understanding to support the development of new targeted therapies. EPoC (Endogenous Perturbation analysis of Cancer) is a network modeling technique for tumor molecular profiles. EPoC models are constructed from combined copy number aberration (CNA) and mRNA data and aim to (1) identify genes whose copy number aberrations significantly affect target mRNA expression and (2) generate markers for long- and short-term survival of cancer patients. Models are constructed by a combination of regression and bootstrapping methods. Prognostic scores are obtained from a singular value decomposition of the networks. We have previously analyzed the performance of EPoC using glioblastoma data from The Cancer Genome Atlas (TCGA) consortium, and have shown that resulting network models contain both known and candidate disease-relevant genes as network hubs, as well as uncover predictors of patient survival. Here, we give a practical guide how to perform EPoC modeling in practice using R, and present a set of alternative modeling frameworks.
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| 6. |
- Barretina, Jordi, et al.
(författare)
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Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy.
- 2010
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Ingår i: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 42:8, s. 715-21
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Tidskriftsartikel (refereegranskat)abstract
- Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.
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| 7. |
- Cvijovic, Marija, 1977, et al.
(författare)
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Bridging the gaps in systems biology
- 2014
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Ingår i: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 289:5, s. 727-734
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Tidskriftsartikel (refereegranskat)abstract
- Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.
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| 8. |
- Gerlee, Philip, 1980, et al.
(författare)
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Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening
- 2013
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:7
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Tidskriftsartikel (refereegranskat)abstract
- Functionally interacting perturbations, such as synergistic drugs pairs or synthetic lethal gene pairs, are of key interest in both pharmacology and functional genomics. However, to find such pairs by traditional screening methods is both time consuming and costly. We present a novel computational-experimental framework for efficient identification of synergistic target pairs, applicable for screening of systems with sizes on the order of current drug, small RNA or SGA (Synthetic Genetic Array) libraries (>1000 targets). This framework exploits the fact that the response of a drug pair in a given system, or a pair of genes' propensity to interact functionally, can be partly predicted by computational means from (i) a small set of experimentally determined target pairs, and (ii) pre-existing data (e.g. gene ontology, PPI) on the similarities between targets. Predictions are obtained by a novel matrix algebraic technique, based on cyclical projections onto convex sets. We demonstrate the efficiency of the proposed method using drug-drug interaction data from seven cancer cell lines and gene-gene interaction data from yeast SGA screens. Our protocol increases the rate of synergism discovery significantly over traditional screening, by up to 7-fold. Our method is easy to implement and could be applied to accelerate pair screening for both animal and microbial systems.
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| 9. |
- Gerlee, Philip, 1980, et al.
(författare)
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The Impact of Phenotypic Switching on Glioblastoma Growth and Invasion
- 2012
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Ingår i: PLoS Computational Biology. - : Public Library of Science (PLoS). - 1553-7358 .- 1553-734X. ; 8:6
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Tidskriftsartikel (refereegranskat)abstract
- The brain tumour glioblastoma is characterised by diffuse and infiltrative growth into surrounding brain tissue. At the macroscopic level, the progression speed of a glioblastoma tumour is determined by two key factors: the cell proliferation rate and the cell migration speed. At the microscopic level, however, proliferation and migration appear to be mutually exclusive phenotypes, as indicated by recent in vivo imaging data. Here, we develop a mathematical model to analyse how the phenotypic switching between proliferative and migratory states of individual cells affects the macroscopic growth of the tumour. For this, we propose an individual-based stochastic model in which glioblastoma cells are either in a proliferative state, where they are stationary and divide, or in motile state in which they are subject to random motion. From the model we derive a continuum approximation in the form of two coupled reaction-diffusion equations, which exhibit travelling wave solutions whose speed of invasion depends on the model parameters. We propose a simple analytical method to predict progression rate from the cell-specific parameters and demonstrate that optimal glioblastoma growth depends on a non-trivial trade-off between the phenotypic switching rates. By linking cellular properties to an in vivo outcome, the model should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.
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| 10. |
- Gerlee, Philip, 1980, et al.
(författare)
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Travelling wave analysis of a mathematical model of glioblastoma growth
- 2016
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Ingår i: Mathematical Biosciences. - : Elsevier BV. - 0025-5564 .- 1879-3134. ; 276, s. 75-81
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we analyse a previously proposed cell-based model of glioblastoma (brain tumour) growth, which is based on the assumption that the cancer cells switch phenotypes between a proliferative and motile state (Gerlee and Nelander, PLoS Comp. Bio., 8(6) 2012). The dynamics of this model can be described by a system of partial differential equations, which exhibits travelling wave solutions whose wave speed depends crucially on the rates of phenotypic switching. We show that under certain conditions on the model parameters, a closed form expression of the wave speed can be obtained, and using singular perturbation methods we also derive an approximate expression of the wave front shape. These new analytical results agree with simulations of the cell-based model, and importantly show that the inverse relationship between wave front steepness and speed observed for the Fisher equation no longer holds when phenotypic switching is considered.
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| 11. |
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| 12. |
- Håkansson, Joakim, 1975, et al.
(författare)
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Neural cell adhesion molecule-deficient beta-cell tumorigenesis results in diminished extracellular matrix molecule expression and tumour cell-matrix adhesion
- 2005
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Ingår i: Tumour Biology. - : Springer Science and Business Media LLC. - 1010-4283 .- 1423-0380. ; 26:2, s. 103-112
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Tidskriftsartikel (refereegranskat)abstract
- To understand by which mechanism neural cell adhesion molecule (N-CAM) limits beta tumour cell disaggregation and dissemination, we searched for potential downstream genes of N-CAM during beta tumour cell progression by gene expression profiling. Here, we show that N-CAM-deficient beta-cell tumorigenesis is associated with changes in the expression of genes involved in cell-matrix adhesion and cytoskeletal dynamics, biological processes known to affect the invasive and metastatic behaviour of tumour cells. The extracellular matrix (ECM) molecules emerged as the primary target, i.e. N-CAM deficiency resulted in down-regulated mRNA expression of a broad range of ECM molecules. Consistent with this result, deficient deposition of major ECM stromal components, such as fibronectin, laminin 1 and collagen IV, was observed. Moreover, N-CAM-deficient tumour cells displayed defective matrix adhesion. These results offer a potential mechanism for tumour cell disaggregation during N-CAM-deficient beta tumour cell progression. Prospective consequences of these findings for the role of N-CAM in beta tumour cell dissemination are discussed.
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| 13. |
- Larsson, Erik, 1975, et al.
(författare)
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Do two mutually exclusive gene modules define the phenotypic diversity of mammalian smooth muscle?
- 2008
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Ingår i: Molecular genetics and genomics : MGG. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 280:2, s. 127-37
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Tidskriftsartikel (refereegranskat)abstract
- Smooth muscle cells (SMCs) are key components of all hollow organs, where they perform contractile, synthetic and other functions. Unlike other muscle cells, SMCs are not terminally differentiated, but exhibit considerable phenotypic variation. Such variation is manifested both across disease states such as asthma and atherosclerosis, and physiological states such as pregnancy and wound healing. While there has been considerable investigation into the diversity of SMCs at the level of morphology and individual biomarkers, less is known about the diversity of SMCs at the level of the transcriptome. To explore this question, we performed an extensive statistical analysis that integrates 200 transcriptional profiles obtained in different SMC phenotypes and reference tissues. Our results point towards a non-trivial hypothesis: that transcriptional variation in different SMC phenotypes is characterized by coordinated differential expression of two mutually exclusive (anti-correlating) gene modules. The first of these modules (C) encodes 19 co-transcribed cell cycle associated genes, whereas the other module (E) encodes 41 co-transcribed extra-cellular matrix components. We propose that the positioning of smooth muscle cells along the C/E axis constitutes an important determinant of SMC phenotypes. In conclusion, our study introduces a new approach to assess phenotypic variation in smooth muscle cells, and is relevant as an example of how integrative bioinformatics analysis can shed light on not only terminal differentiated states but also subtler details in phenotypic variability. It also raises the broader question whether coordinated expression of gene modules is a common mechanism underlying phenotypic variability in mammalian cells.
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| 14. |
- Matuszewski, Damian J., et al.
(författare)
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Image-Based Detection of Patient-Specific Drug-Induced Cell-Cycle Effects in Glioblastoma
- 2018
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Ingår i: SLAS Discovery. - : Elsevier BV. - 2472-5560 .- 2472-5552. ; 23:10, s. 1030-1039
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Tidskriftsartikel (refereegranskat)abstract
- Image-based analysis is an increasingly important tool to characterize the effect of drugs in large-scale chemical screens. Herein, we present image and data analysis methods to investigate population cell-cycle dynamics in patient-derived brain tumor cells. Images of glioblastoma cells grown in multiwell plates were used to extract per-cell descriptors, including nuclear DNA content. We reduced the DNA content data from per-cell descriptors to per-well frequency distributions, which were used to identify compounds affecting cell-cycle phase distribution. We analyzed cells from 15 patient cases representing multiple subtypes of glioblastoma and searched for clusters of cell-cycle phase distributions characterizing similarities in response to 249 compounds at 11 doses. We show that this approach applied in a blind analysis with unlabeled substances identified drugs that are commonly used for treating solid tumors as well as other compounds that are well known for inducing cell-cycle arrest. Redistribution of nuclear DNA content signals is thus a robust metric of cell-cycle arrest in patient-derived glioblastoma cells.
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| 15. |
- Nelander, Sven, 1974
(författare)
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A genomic approach to smooth muscle differentiation and diversity
- 2005
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Smooth muscle cells (SMCs) are a broad class of contractile cells that are found in a number of organs systems, including the vasculature, the urogenital system, the bronchi and the gastrointestinal tract. The two main functions exerted by SMCs are to provide contractile force and to synthesize structural components of the extracellular matrix. SMCs are not terminally differentiated, but have a capacity to adjust their cellular phenotype to meet crucial physiological needs. Examples include repair of blood vessels, and uterine growth during pregnancy. In addition, SMC plasticity may be important in human diseases such as asthma, pre-term delivery, atherosclerosis, and hypertension. A great challenge in smooth muscle biology is therefore to identify molecular mechanisms that mediate SMC phenotypic differences. The aim of the present study is to examine SMC differentiation and diversity in terms of global gene expression. In general terms, we ask how genome sequences and large-scale observations of gene expression patterns together can be used to define and understand SMC differentiation and diversity. Three lines of investigation are followed. First, we examine gene expression patterns of SMC subpopulations using gene chip technology, which results in a transcription atlas of SMC diversity (I, IV). Second, we propose a general approach to the functional and regulatory interpretation of such data, based on the biological concept of gene batteries defined as sets of genes that are co-regulated and functionally linked (II, III). This approach is general, and applicable beyond SMC biology. Third, we use this framework to interpret our exploration of SMC phenotypes, and to postulate regulators of SMC phenotypic diversity (III, IV). We find evidence that that several gene batteries are synchronously regulated during vascular SMC maturation and neointima formation, suggesting that distinct features of the vascular SMC phenotype are encoded by individual gene batteries (IV). Among regulated gene batteries, a lipid metabolism battery and a vascular-selective extracellular matrix battery are found. Regulatory sequence analysis was performed on a whole-genome scale with respect to 266 DNA-binding transcription factors, and results were used to predict cis regulatory elements of importance for gene batteries and vascular SMC marker genes (III, IV). Specific findings include novel SMC differentiation markers, including LPP, a potential SMC-selective transcriptional regulator (II). In summary, the work provides a genomic formulation of the SMC differentiation and diversity problem, and proposes a model for the SMC phenotype which is based on explicitly defined groups of genes.
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| 16. |
- Nelander, Sven, 1974, et al.
(författare)
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Prediction of cell type-specific gene modules: identification and initial characterization of a core set of smooth muscle-specific genes.
- 2003
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Ingår i: Genome research. - : Cold Spring Harbor Laboratory. - 1088-9051 .- 1549-5469. ; 13:8, s. 1838-54
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Tidskriftsartikel (refereegranskat)abstract
- Genes that are expressed in the same subset of cells potentially constitute a module regulated by shared cis-regulatory elements and a distinct set of transcription factors. Identifying such units is an important entry point to the molecular study of cell differentiation. We developed a general method to classify cell type-specific genes from expressed sequence tag (EST) data, and we optimized it for identification of smooth muscle cell (SMC)-specific genes. Expression profiles were derived from the quantitative distribution of EST data in mouse, and genes were classified based on their profile similarity to known reference genes, in this case smooth muscle myosin heavy chain. A large majority (>90%) of known SMC-specific genes were identified, together with novel candidates. Extensive experimental validation confirmed SMC-specific expression of candidates, for example, lipoma preferred partner (LPP) and a novel SMC-specific putative monoamine oxidase, SMAO. Our method performed considerably better than other computational methods in an objective cross validation comparison. The total number of SMC-specific genes is estimated to be approximately 50.
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| 17. |
- Nelander, Sven, 1974, et al.
(författare)
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Predictive screening for regulators of conserved functional gene modules (gene batteries) in mammals
- 2005
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Ingår i: BMC genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The expression of gene batteries, genomic units of functionally linked genes which are activated by similar sets of cis- and trans-acting regulators, has been proposed as a major determinant of cell specialization in metazoans. We developed a predictive procedure to screen the mouse and human genomes and transcriptomes for cases of gene-battery-like regulation. RESULTS: In a screen that covered approximately 40 percent of all annotated protein-coding genes, we identified 21 co-expressed gene clusters with statistically supported sharing of cis-regulatory sequence elements. 66 predicted cases of over-represented transcription factor binding motifs were validated against the literature and fell into three categories: (i) previously described cases of gene battery-like regulation, (ii) previously unreported cases of gene battery-like regulation with some support in a limited number of genes, and (iii) predicted cases that currently lack experimental support. The novel predictions include for example Sox 17 and RFX transcription factor binding sites that were detected in approximately 10% of all testis specific genes, and HNF-1 and 4 binding sites that were detected in approximately 30% of all kidney specific genes respectively. The results are publicly available at http://www.wlab.gu.se/lindahl/genebatteries. CONCLUSION: 21 co-expressed gene clusters were enriched for a total of 66 shared cis-regulatory sequence elements. A majority of these predictions represent novel cases of potential co-regulation of functionally coupled proteins. Critical technical parameters were evaluated, and the results and the methods provide a valuable resource for future experimental design.
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| 18. |
- Persson, Marta, 1979, et al.
(författare)
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Clinically significant copy number alterations and complex rearrangements of MYB and NFIB in head and neck adenoid cystic carcinoma.
- 2012
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Ingår i: Genes, chromosomes & cancer. - : Wiley. - 1098-2264 .- 1045-2257. ; 51:8, s. 805-17
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Tidskriftsartikel (refereegranskat)abstract
- Adenoid cystic carcinoma (ACC) of the head and neck is a malignant tumor with poor long-term prognosis. Besides the recently identified MYB-NFIB fusion oncogene generated by a t(6;9) translocation, little is known about other genetic alterations in ACC. Using high-resolution, array-based comparative genomic hybridization, and massively paired-end sequencing, we explored genomic alterations in 40 frozen ACCs. Eighty-six percent of the tumors expressed MYB-NFIB fusion transcripts and 97% overexpressed MYB mRNA, indicating that MYB activation is a hallmark of ACC. Thirty-five recurrent copy number alterations (CNAs) were detected, including losses involving 12q, 6q, 9p, 11q, 14q, 1p, and 5q and gains involving 1q, 9p, and 22q. Grade III tumors had on average a significantly higher number of CNAs/tumor compared to Grade I and II tumors (P = 0.007). Losses of 1p, 6q, and 15q were associated with high-grade tumors, whereas losses of 14q were exclusively seen in Grade I tumors. The t(6;9) rearrangements were associated with a complex pattern of breakpoints, deletions, insertions, inversions, and for 9p also gains. Analyses of fusion-negative ACCs using high-resolution arrays and massively paired-end sequencing revealed that MYB may also be deregulated by other mechanisms in addition to gene fusion. Our studies also identified several down-regulated candidate tumor suppressor genes (CTNNBIP1, CASP9, PRDM2, and SFN) in 1p36.33-p35.3 that may be of clinical significance in high-grade tumors. Further, studies of these and other potential target genes may lead to the identification of novel driver genes in ACC.
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| 19. |
- Schultz, Nikolaus, et al.
(författare)
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Off-target effects dominate a large-scale RNAi screen for modulators of the TGF-beta pathway and reveal microRNA regulation of TGFBR2
- 2011
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Ingår i: Silence. - 1758-907X. ; 14:2
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Tidskriftsartikel (refereegranskat)abstract
- Abstract Background RNA interference (RNAi) screens have been used to identify novel components of signal-transduction pathways in a variety of organisms. We performed a small interfering (si)RNA screen for novel members of the transforming growth factor (TGF)-β pathway in a human keratinocyte cell line. The TGF-β pathway is integral to mammalian cell proliferation and survival, and aberrant TGF-β responses have been strongly implicated in cancer. Results We assayed how strongly single siRNAs targeting each of 6,000 genes affect the nuclear translocation of a green fluorescent protein (GFP)-SMAD2 reporter fusion protein. Surprisingly, we found no novel TGF-β pathway members, but we did find dominant off-target effects. All siRNA hits, whatever their intended direct target, reduced the mRNA levels of two known upstream pathway components, the TGF-β receptors 1 and 2 (TGFBR1 and TGFBR2), via micro (mi)RNA-like off-target effects. The scale of these off-target effects was remarkable, with at least 1% of the sequences in the unbiased siRNA library having measurable off-target effects on one of these two genes. It seems that relatively minor reductions of message levels via off-target effects can have dominant effects on an assay, if the pathway output is very dose-sensitive to levels of particular pathway components. In search of mechanistic details, we identified multiple miRNA-like sequence characteristics that correlated with the off-target effects. Based on these results, we identified miR-20a, miR-34a and miR-373 as miRNAs that inhibit TGFBR2 expression. Conclusions Our findings point to potential improvements for miRNA/siRNA target prediction methods, and suggest that the type II TGF-β receptor is regulated by multiple miRNAs. We also conclude that the risk of obtaining misleading results in siRNA screens using large libraries with single-assay readout is substantial. Control and rescue experiments are essential in the interpretation of such screens, and improvements to the methods to reduce or predict RNAi off-target effects would be beneficial.
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