Ultrasensitive amplification-free quantification of a methyl CpG-rich cancer biomarker by single-molecule kinetic fingerprinting.

The most well-studied epigenetic marker in humans is the 5-methyl modification of cytosine in DNA, which has great potential as a disease biomarker in liquid biopsies of cell-free DNA. Currently, quantification of DNA methylation relies heavily on bisulfite conversion followed by PCR amplification and NGS or microarray analysis. PCR is subject to potential bias in differential amplification of bisulfite-converted methylated versus unmethylated sequences. Here, we combine bisulfite conversion with single-molecule kinetic fingerprinting to develop an amplification-free assay for DNA methylation at the branched-chain amino acid transaminase 1 (BCAT1) promoter. Our assay selectively responds to methylated sequences with a limit of detection below 1 fM and a specificity of 99.9999%. Evaluating complex genomic DNA matrices, we reliably distinguish 2-5% DNA methylation at the BCAT1 promoter in whole blood DNA from completely unmethylated whole-genome amplified DNA. Taken together, these results demonstrate the feasibility and sensitivity of our amplification-free, single-molecule quantification approach to improve the early detection of methylated cancer DNA biomarkers.

BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies.

Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.

DAB2IP Is a Bifunctional Tumor Suppressor That Regulates Wild-Type RAS and Inflammatory Cascades in KRAS Mutant Colon Cancer.

The DAB2IP tumor suppressor encodes a RAS GTPase-activating protein. Accordingly, DAB2IP has been shown to be mutated or suppressed in tumor types that typically lack RAS mutations. However, here we report that DAB2IP is mutated or selectively silenced in the vast majority of KRAS and BRAF mutant colorectal cancers. In this setting, DAB2IP loss promoted tumor development by activating wild-type H- and N-RAS proteins, which was surprisingly required to achieve robust activation of RAS effector pathways in KRAS-mutant tumors. DAB2IP loss also triggered production of inflammatory mediators and the recruitment of protumorigenic macrophages in vivo. Importantly, tumor growth was suppressed by depleting macrophages or inhibiting cytokine/inflammatory mediator expression with a JAK/TBK1 inhibitor. In human tumors, DAB2IP was lost at early stages of tumor development, and its depletion was associated with an enrichment of macrophage and inflammatory signatures. Together, these findings demonstrate that DAB2IP restrains the activation of the RAS pathway and inflammatory cascades in the colon and that its loss represents a common and unappreciated mechanism for amplifying these two critical oncogenic signals in colorectal cancer. SIGNIFICANCE: DAB2IP is lost in early-stage tumors, which amplifies RAS signaling, triggers inflammatory mediators, and recruits macrophages in KRAS-mutant colon cancers.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer's Disease.

Alzheimer's disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer's disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein-protein network characterized by inverse RNA/DNA methylation correlation and enriched for "Regulation of insulin-like growth factor transport", with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.

Comprehensive Evaluation of The Infinium Human MethylationEPIC v2 BeadChip.

Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.

Cell division drives DNA methylation loss in late-replicating domains in primary human cells.

DNA methylation undergoes dramatic age-related changes, first described more than four decades ago. Loss of DNA methylation within partially methylated domains (PMDs), late-replicating regions of the genome attached to the nuclear lamina, advances with age in normal tissues, and is further exacerbated in cancer. We present here experimental evidence that this DNA hypomethylation is directly driven by proliferation-associated DNA replication. Within PMDs, loss of DNA methylation at low-density CpGs in A:T-rich immediate context (PMD solo-WCGWs) tracks cumulative population doublings in primary cell culture. Cell cycle deceleration results in a proportional decrease in the rate of DNA hypomethylation. Blocking DNA replication via Mitomycin C treatment halts methylation loss. Loss of methylation continues unabated after TERT immortalization until finally reaching a severely hypomethylated equilibrium. Ambient oxygen culture conditions increases the rate of methylation loss compared to low-oxygen conditions, suggesting that some methylation loss may occur during unscheduled, oxidative damage repair-associated DNA synthesis. Finally, we present and validate a model to estimate the relative cumulative replicative histories of human cells, which we call "RepliTali" (Replication Times Accumulated in Lifetime).

High-Resolution Profiling of Lung Adenocarcinoma Identifies Expression Subtypes with Specific Biomarkers and Clinically Relevant Vulnerabilities.

Lung adenocarcinoma (LUAD) is one of the most common cancer types and has various treatment options. Better biomarkers to predict therapeutic response are needed to guide choice of treatment modality and to improve precision medicine. Here, we used a consensus hierarchical clustering approach on 509 LUAD cases from The Cancer Genome Atlas to identify five robust LUAD expression subtypes. Genomic and proteomic data from patient samples and cell lines was then integrated to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles. Subtype 4 (S4)-associated cell lines exhibited specific vulnerability to loss of CDK6 and CDK6-cyclin D3 complex gene (CCND3). Subtype 3 (S3) was characterized by dependency on CDK4, immune-related expression patterns, and altered MET signaling. Experimental validation showed that S3-associated cell lines responded to MET inhibitors, leading to increased expression of programmed death-ligand 1 (PD-L1). In an independent real-world patient dataset, patients with S3 tumors were enriched with responders to immune checkpoint blockade. Genomic features in S3 and S4 were further identified as biomarkers for enabling clinical diagnosis of these subtypes. Overall, our consensus hierarchical clustering approach identified robust tumor expression subtypes, and our subsequent integrative analysis of genomics, proteomics, and CRISPR screening data revealed subtype-specific biology and vulnerabilities. These LUAD expression subtypes and their biomarkers could help identify patients likely to respond to CDK4/6, MET, or PD-L1 inhibitors, potentially improving patient outcome. SIGNIFICANCE: Integrative analysis of multiomic and drug dependency data uncovers robust lung adenocarcinoma expression subtypes with unique therapeutic vulnerabilities and subtype-specific biomarkers of response.

DNA methylation dynamics and dysregulation delineated by high-throughput profiling in the mouse.

We have developed a mouse DNA methylation array that contains 296,070 probes representing the diversity of mouse DNA methylation biology. We present a mouse methylation atlas as a rich reference resource of 1,239 DNA samples encompassing distinct tissues, strains, ages, sexes, and pathologies. We describe applications for comparative epigenomics, genomic imprinting, epigenetic inhibitors, patient-derived xenograft assessment, backcross tracing, and epigenetic clocks. We dissect DNA methylation processes associated with differentiation, aging, and tumorigenesis. Notably, we find that tissue-specific methylation signatures localize to binding sites for transcription factors controlling the corresponding tissue development. Age-associated hypermethylation is enriched at regions of Polycomb repression, while hypomethylation is enhanced at regions bound by cohesin complex members. Apc Min/+ polyp-associated hypermethylation affects enhancers regulating intestinal differentiation, while hypomethylation targets AP-1 binding sites. This Infinium Mouse Methylation BeadChip (version MM285) is widely accessible to the research community and will accelerate high-sample-throughput studies in this important model organism.

How epigenomics broke the mold: an interview with Peter W Laird.

In this interview, Professor Peter W Laird speaks with Storm Johnson, Commissioning Editor for Epigenomics, on his work to date in the field of cancer epigenetics. Dr Peter W Laird is a Professor at Van Andel Institute (VAI) in Grand Rapids, Michigan. He earned his B.S. and M.S., Cum Laude, from the University of Leiden, The Netherlands. He trained for his PhD with Dr Piet Borst, The Netherlands Cancer Institute, and as a postdoc with Dr Anton Berns, The Netherlands Cancer Institute, and with Dr Rudolf Jaenisch, at the Whitehead Institute for Biomedical Research in Cambridge, MA, USA. He joined the faculty at the University of Southern California in 1996, where he served as the Founding Director of the USC Epigenome Center and also as the Leader of the Epigenetics and Regulation Program of the Norris Comprehensive Cancer Center. In 2014, he relocated to VAI to join Dr Peter Jones in building an internationally acclaimed research center focused on Epigenetics. Dr Laird published the first demonstration of the causal role for DNA methylation in oncogenesis (Cell, 1995) [1]. He served as the Principal Investigator for all DNA methylation data production for the Cancer Genome Atlas (TCGA) and led many TCGA analysis efforts. He has been awarded 10 patents related to DNA methylation technology by the United States Patent and Trademark Office, one of which is the basis for the first US FDA-approved blood-based DNA methylation assay for cancer (Epi proColon). His research findings include the report of a close link between DNA methylation and BRAF mutation in colorectal cancer (Nature Genetics, 2006) [2], the discovery that embryonic stem cell polycomb repressor targets are predisposed to abnormal DNA methylation in cancer (Nature Genetics, 2007) [3], the identification of a novel epigenetic subtype of glioma (G-CIMP), tightly associated with IDH1 mutation (Cancer Cell, 2010) [4], and the connection between nuclear architecture, late replication, and domains of epigenetic instability (Nature Genetics, 2011) [5], later showing a link with mitotic cell division, thus providing a mechanistic explanation for the loss of DNA methylation in aging and cancer first described four decades ago (Nature Genetics, 2018) [6].

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

The Exceptional Responders Initiative: Feasibility of a National Cancer Institute Pilot Study.

BACKGROUND: Tumor molecular profiling from patients experiencing exceptional responses to systemic therapy may provide insights into cancer biology and improve treatment tailoring. This pilot study evaluates the feasibility of identifying exceptional responders retrospectively, obtaining pre-exceptional response treatment tumor tissues, and analyzing them with state-of-the-art molecular analysis tools to identify potential molecular explanations for responses. METHODS: Exceptional response was defined as partial (PR) or complete (CR) response to a systemic treatment with population PR or CR rate less than 10% or an unusually long response (eg, duration >3 times published median). Cases proposed by patients' clinicians were reviewed by clinical and translational experts. Tumor and normal tissue (if possible) were profiled with whole exome sequencing and, if possible, targeted deep sequencing, RNA sequencing, methylation arrays, and immunohistochemistry. Potential germline mutations were tracked for relevance to disease. RESULTS: Cases reflected a variety of tumors and standard and investigational treatments. Of 520 cases, 476 (91.5%) were accepted for further review, and 222 of 476 (46.6%) proposed cases met requirements as exceptional responders. Clinical data were obtained from 168 of 222 cases (75.7%). Tumor was provided from 130 of 168 cases (77.4%). Of 117 of the 130 (90.0%) cases with sufficient nucleic acids, 109 (93.2%) were successfully analyzed; 6 patients had potentially actionable germline mutations. CONCLUSION: Exceptional responses occur with standard and investigational treatment. Retrospective identification of exceptional responders, accessioning, and sequencing of pretreatment archived tissue is feasible. Data from molecular analyses of tumors, particularly when combining results from patients who received similar treatments, may elucidate molecular bases for exceptional responses.

Molecular Features of Cancers Exhibiting Exceptional Responses to Treatment.

A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories-DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis-with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.

Phase I trial of TRC102 (methoxyamine HCl) in combination with temozolomide in patients with relapsed solid tumors and lymphomas.

BACKGROUND: TRC102 inhibits base excision repair by binding abasic sites and preventing AP endonuclease processing; it potentiates the activity of alkylating agents, including temozolomide, in murine models. In published xenograft studies, TRC102 enhanced the antitumor effect of temozolomide regardless of cell line genetic characteristics, e.g., O6-methylguanine DNA methyltransferase (MGMT), mismatch repair (MMR), or p53 status. MATERIALS AND METHODS: We conducted a phase 1 trial of TRC102 with temozolomide given orally on days 1-5 of 28-day cycles in adult patients with refractory solid tumors that had progressed on standard therapy. Tumor induction of nuclear biomarkers of DNA damage response (DDR) γH2AX, pNBs1, and Rad51 was assessed in the context of MGMT and MMR protein expression for expansion cohort patients. RESULTS: Fifty-two patients were enrolled (37 escalation, 15 expansion) with 51 evaluable for response. The recommended phase 2 dose was 125 mg TRC102, 150 mg/m2 temozolomide QDx5. Common adverse events (grade 3/4) included anemia (19%), lymphopenia (12%), and neutropenia (10%). Four patients achieved partial responses (1 non-small cell lung cancer, 2 granulosa cell ovarian cancer, and 1 colon cancer) and 13 patients had a best response of stable disease. Retrospective analysis of 15 expansion cohort patients did not demonstrate a correlation between low tumor MGMT expression and patient response, but treatment induced nuclear Rad51 responses in 6 of 12 patients. CONCLUSIONS: The combination of TRC 102 with temozolomide is active, with 4 of 51 patients experiencing a partial response and 13 of 51 experiencing stable disease, and the side effect profile is manageable.

Systematic Assessment of Tumor Purity and Its Clinical Implications.

PURPOSE: The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor. MATERIALS AND METHODS: To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles. RESULTS: We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types. CONCLUSION: The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.

Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer.

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

Differences in Genome-wide DNA Methylation Profiles in Breast Milk by Race and Lactation Duration.

Black women in the United States are disproportionately affected by early-onset, triple-negative breast cancer. DNA methylation has shown differences by race in healthy and tumor breast tissues. We examined associations between genome-wide DNA methylation levels in breast milk and breast cancer risk factors, including race, to explain how this reproductive stage influences a woman's risk for, and potentially contributes to racial disparities in, breast cancer. Breast milk samples and demographic, behavioral, and reproductive data, were obtained from cancer-free, uniparous, and lactating U.S. black (n = 57) and white (n = 82) women, ages 19-44. Genome-wide DNA methylation analysis was performed on extracted breast milk DNA using the Infinium HumanMethylation450 BeadChip. Statistically significant associations between breast cancer risk factors and DNA methylation beta values, adjusting for potential confounders, were determined using linear regression followed by Bonferroni Correction (P < 1.63 × 10-7). Epigenetic analysis in breast milk revealed statistically significant associations with race and lactation duration. Of the 284 CpG sites associated with race, 242 were hypermethylated in black women. All 227 CpG sites associated with lactation duration were hypomethylated in women who lactated longer. Ingenuity Pathway Analysis of differentially methylated promoter region CpGs by race and lactation duration revealed enrichment for networks implicated in carcinogenesis. Associations between DNA methylation and lactation duration may offer insight on its role in lowering breast cancer risk. Epigenetic associations with race may mediate social, behavioral, or other factors related to breast cancer and may provide insight into potential mechanisms underlying racial disparities in breast cancer incidence.

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data.

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA).

Rational: LDCT screening can identify early-stage lung cancers yet introduces excessive false positives and it remains a great challenge to differentiate malignant tumors from benign solitary pulmonary nodules, which calls for better non-invasive diagnostic tools. Methods: We performed DNA methylation profiling by high throughput DNA bisulfite sequencing in tissue samples (nodule size < 3 cm in diameter) to learn methylation patterns that differentiate cancerous tumors from benign lesions. Then we filtered out methylation patterns exhibiting high background in circulating tumor DNA (ctDNA) and built an assay for plasma sample classification. Results: We first performed methylation profiling of 230 tissue samples to learn cancer-specific methylation patterns which achieved a sensitivity of 92.7% (88.3% - 97.1%) and a specificity of 92.8% (89.3% - 96.3%). These tissue-derived DNA methylation markers were further filtered using a training set of 66 plasma samples and 9 markers were selected to build a diagnostic prediction model. From an independent validation set of additional 66 plasma samples, this model obtained a sensitivity of 79.5% (63.5% - 90.7%) and a specificity of 85.2% (66.3% - 95.8%) for differentiating patients with malignant tumor (n = 39) from patients with benign lesions (n = 27). Additionally, when tested on gender and age matched asymptomatic normal individuals (n = 118), our model achieved a specificity of 93.2% (89.0% - 98.3%). Specifically, our assay is highly sensitive towards early-stage lung cancer, with a sensitivity of 75.0% (55.0%-90.0%) in 20 stage Ia lung cancer patients and 85.7% (57.1%-100.0%) in 7 stage Ib lung cancer patients. Conclusions: We have developed a novel sensitive blood based non-invasive diagnostic assay for detecting early stage lung cancer as well as differentiating lung cancers from benign pulmonary nodules.

In vivo Application of the REMOTE-control System for the Manipulation of Endogenous Gene Expression.

Here we describe a protocol for implementing the REMOTE-control system (Reversible Manipulation of Transcription at Endogenous loci), which allows for reversible and tunable expression control of an endogenous gene of interest in living model systems. The REMOTE-control system employs enhanced lac repression and tet activation systems to achieve down- or upregulation of a target gene within a single biological system. Tight repression can be achieved from repressor binding sites flexibly located far downstream of a transcription start site by inhibiting transcription elongation. Robust upregulation can be attained by enhancing the transcription of an endogenous gene by targeting tet transcriptional activators to the cognate promoter. This reversible and tunable expression control can be applied and withdrawn repeatedly in organisms. The potency and versatility of the system, as demonstrated for endogenous Dnmt1 here, will allow more precise in vivo functional analyses by enabling investigation of gene function at various expression levels and by testing the reversibility of a phenotype.