Single-cell transcriptomics reveals immune suppression and cell states predictive of patient outcomes in rhabdomyosarcoma.

Paediatric rhabdomyosarcoma (RMS) is a soft tissue malignancy of mesenchymal origin that is thought to arise as a consequence of derailed myogenic differentiation. Despite intensive treatment regimens, the prognosis for high-risk patients remains dismal. The cellular differentiation states underlying RMS and how these relate to patient outcomes remain largely elusive. Here, we use single-cell mRNA sequencing to generate a transcriptomic atlas of RMS. Analysis of the RMS tumour niche reveals evidence of an immunosuppressive microenvironment. We also identify a putative interaction between NECTIN3 and TIGIT, specific to the more aggressive fusion-positive (FP) RMS subtype, as a potential cause of tumour-induced T-cell dysfunction. In malignant RMS cells, we define transcriptional programs reflective of normal myogenic differentiation and show that these cellular differentiation states are predictive of patient outcomes in both FP RMS and the less aggressive fusion-negative subtype. Our study reveals the potential of therapies targeting the immune microenvironment of RMS and suggests that assessing tumour differentiation states may enable a more refined risk stratification.

Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes.

Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here, we describe the generation of a collection of 19 pediatric RMS tumor organoid (tumoroid) models (success rate of 41%) comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within 4-8 weeks, indicating the feasibility of personalized drug screening. Molecular, genetic, and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to 6 months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions.

Genome-wide off-rates reveal how DNA binding dynamics shape transcription factor function.

Protein-DNA interactions are dynamic, and these dynamics are an important aspect of chromatin-associated processes such as transcription or replication. Due to a lack of methods to study on- and off-rates across entire genomes, protein-DNA interaction dynamics have not been studied extensively. Here, we determine in vivo off-rates for the Saccharomyces cerevisiae chromatin organizing factor Abf1, at 191 sites simultaneously across the yeast genome. Average Abf1 residence times span a wide range, varying between 4.2 and 33 min. Sites with different off-rates are associated with different functional characteristics. This includes their transcriptional dependency on Abf1, nucleosome positioning and the size of the nucleosome-free region, as well as the ability to roadblock RNA polymerase II for termination. The results show how off-rates contribute to transcription factor function and that DIVORSEQ (Determining In Vivo Off-Rates by SEQuencing) is a meaningful way of investigating protein-DNA binding dynamics genome-wide.

An Optimized Chromatin Immunoprecipitation Protocol for Quantification of Protein-DNA Interactions.

Transcription factors are important regulators of cell fate and function. Knowledge about where transcription factors are bound in the genome is crucial for understanding their function. A common method to study protein-DNA interactions is chromatin immunoprecipitation (ChIP). Here, we present a revised ChIP protocol to determine protein-DNA interactions for the yeast Saccharomyces cerevisiae. We optimized several aspects of the procedure, including cross-linking and quenching, cell lysis, and immunoprecipitation steps. This protocol facilitates sensitive and reproducible quantitation of protein-DNA interactions. For complete details on the use and execution of this protocol, please refer to (de Jonge et al., 2019).

A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions.

BACKGROUND: Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering pathway organization and understanding the relationship between genotype, phenotype and disease. RESULTS: To investigate the nature of genetic interactions between gene-specific transcription factors (GSTFs) in Saccharomyces cerevisiae, we systematically analyzed 72 GSTF pairs by gene expression profiling double and single deletion mutants. These pairs were selected through previously published growth-based genetic interactions as well as through similarity in DNA binding properties. The result is a high-resolution atlas of gene expression-based genetic interactions that provides systems-level insight into GSTF epistasis. The atlas confirms known genetic interactions and exposes new ones. Importantly, the data can be used to investigate mechanisms that underlie individual genetic interactions. Two molecular mechanisms are proposed, "buffering by induced dependency" and "alleviation by derepression". CONCLUSIONS: These mechanisms indicate how negative genetic interactions can occur between seemingly unrelated parallel pathways and how positive genetic interactions can indirectly expose parallel rather than same-pathway relationships. The focus on GSTFs is important for understanding the transcription regulatory network of yeast as it uncovers details behind many redundancy relationships, some of which are completely new. In addition, the study provides general insight into the complex nature of epistasis and proposes mechanistic models for genetic interactions, the majority of which do not fall into easily recognizable within- or between-pathway relationships.

Cell cycle population effects in perturbation studies.

Growth condition perturbation or gene function disruption are commonly used strategies to study cellular systems. Although it is widely appreciated that such experiments may involve indirect effects, these frequently remain uncharacterized. Here, analysis of functionally unrelated Saccharyomyces cerevisiae deletion strains reveals a common gene expression signature. One property shared by these strains is slower growth, with increased presence of the signature in more slowly growing strains. The slow growth signature is highly similar to the environmental stress response (ESR), an expression response common to diverse environmental perturbations. Both environmental and genetic perturbations result in growth rate changes. These are accompanied by a change in the distribution of cells over different cell cycle phases. Rather than representing a direct expression response in single cells, both the slow growth signature and ESR mainly reflect a redistribution of cells over different cell cycle phases, primarily characterized by an increase in the G1 population. The findings have implications for any study of perturbation that is accompanied by growth rate changes. Strategies to counter these effects are presented and discussed.

Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.

To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.

Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases.

BACKGROUND AND OBJECTIVES: This study was designed to identify and validate gene signatures that can predict disease free survival (DFS) in patients undergoing a radical resection for their colorectal liver metastases (CRLM). METHODS: Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France) and the University Medical Center Utrecht (The Netherlands). Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort. RESULT: No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort. CONCLUSIONS: No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

The specificity and topology of chromatin interaction pathways in yeast.

Packaging of DNA into chromatin has a profound impact on gene expression. To understand how changes in chromatin influence transcription, we analyzed 165 mutants of chromatin machinery components in Saccharomyces cerevisiae. mRNA expression patterns change in 80% of mutants, always with specific effects, even for loss of widespread histone marks. The data are assembled into a network of chromatin interaction pathways. The network is function based, has a branched, interconnected topology, and lacks strict one-to-one relationships between complexes. Chromatin pathways are not separate entities for different gene sets, but share many components. The study evaluates which interactions are important for which genes and predicts additional interactions, for example between Paf1C and Set3C, as well as a role for Mediator in subtelomeric silencing. The results indicate the presence of gene-dependent effects that go beyond context-dependent binding of chromatin factors and provide a framework for understanding how specificity is achieved through regulating chromatin.

Functional overlap and regulatory links shape genetic interactions between signaling pathways.

To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.

Improved genome-wide localization by ChIP-chip using double-round T7 RNA polymerase-based amplification.

Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a powerful technique to detect in vivo protein-DNA interactions. Due to low yields, ChIP assays of transcription factors generally require amplification of immunoprecipitated genomic DNA. Here, we present an adapted linear amplification method that involves two rounds of T7 RNA polymerase amplification (double-T7). Using this we could successfully amplify as little as 0.4 ng of ChIP DNA to sufficient amounts for microarray analysis. In addition, we compared the double-T7 method to the ligation-mediated polymerase chain reaction (LM-PCR) method in a ChIP-chip of the yeast transcription factor Gsm1p. The double-T7 protocol showed lower noise levels and stronger binding signals compared to LM-PCR. Both LM-PCR and double-T7 identified strongly bound genomic regions, but the double-T7 method increased sensitivity and specificity to allow detection of weaker binding sites.

Chronic imatinib mesylate exposure leads to reduced intracellular drug accumulation by induction of the ABCG2 (BCRP) and ABCB1 (MDR1) drug transport pumps.

Imatinib mesylate is a selective tyrosine kinase inhibitor that is successfully used in the treatment of Philadelphia-positive chronic and acute leukaemia's, and gastrointestinal stromal tumors. We investigated whether the intended chronic oral administration of imatinib might lead to the induction of the intestinal ABC transport proteins ABCB1, ABCC1 (MRP1), ABCC2 (MRP2) and ABCG2. Using Caco2 cells as an in vitro model for intestinal drug transport, we found that continuous exposure (up to 100 days) with imatinib (10 microM) specifically upregulates the expression of ABCG2 (maximal approximately 17-fold) and ABCB1 (maximal approximately 5-fold). The induction of gene expression appeared to be biphasic in time, with a significant increase in ABCG2 and ABCB1 at day 3 and day 25, respectively, and was not mediated through activation of the human orphan nuclear receptor SXR/NR1I2. Importantly, chronic imatinib exposure of Caco2 cells resulted in a approximately 50% decrease in intracellular accumulation of imatinib, probably by enhanced ABCG2- and ABCB1-mediated efflux, as a result of upregulated expression of these drug pumps. Both ABCG2 and ABCB1 are normally expressed in the gastrointestinal tract and it might be anticipated that drug-induced upregulation of these intestinal pumps could reduce the oral bioavailability of imatinib, representing a novel mechanism of acquired pharmacokinetic drug resistance in cancer patients that are chronically treated with imatinib.

Imatinib mesylate (STI571) is a substrate for the breast cancer resistance protein (BCRP)/ABCG2 drug pump.

Imatinib mesylate (STI571), a potent tyrosine kinase inhibitor, is successfully used in the treatment of chronic myelogenous leukemia and gastrointestinal stromal tumors. However, the intended chronic oral administration of imatinib may lead to development of cellular resistance and subsequent treatment failure. Indeed, several molecular mechanisms leading to imatinib resistance have already been reported, including overexpression of the MDR1/ABCB1 drug pump. We examined whether imatinib is a substrate for the breast cancer resistance protein (BCRP)/ABCG2 drug pump that is frequently overexpressed in human tumors. Using a panel of well-defined BCRP-overexpressing cell lines, we provide the first evidence that imatinib is a substrate for BCRP, that it competes with mitoxantrone for drug export, and that BCRP-mediated efflux can be reversed by the fumitremorgin C analog Ko-143. Since BCRP is highly expressed in the gastrointestinal tract, BCRP might not only play a role in cellular resistance of tumor cells but also influence the gastrointestinal absorption of imatinib.

Anticancer drug resistance induced by disruption of the Saccharomyces cerevisiae NPR2 gene: a novel component involved in cisplatin- and doxorubicin-provoked cell kill.

The therapeutic potential of antitumor drugs is seriously limited by the manifestation of cellular drug resistance. We used the budding yeast Saccharomyces cerevisiae as a model system to identify novel mechanisms of resistance to one of the most active anticancer agents, cisplatin. We pinpointed NPR2 (nitrogen permease regulator 2) as a gene whose disruption conferred resistance to cisplatin. In addition, we observed a 4-fold cross-resistance of yeast npr2Delta cells (i.e., cells from which the NPR2 gene had been disrupted) to the anticancer drug doxorubicin, in combination with hypersensitivity to cadmium chloride. Furthermore, npr2Delta cells displayed unaltered cellular cisplatin and doxorubicin accumulation and showed an enhanced rate of spontaneous mutation compared with the isogenic parent. These data indicate that the npr2Delta phenotype overlaps that of the sky1Delta cells that we characterized previously (Mol Pharmacol 61:659-666, 2002). Therefore, we generated yeast npr2Delta sky1Delta double-knockout cells and performed clonogenic survival assays for cisplatin and doxorubicin, which revealed that NPR2 and SKY1 (SR-protein-specific kinase from budding yeast) are epistatic. The double-knockout strain was just as resistant to cisplatin and doxorubicin as the single-knockout strain that was most resistant to either drug. In conclusion, we identified NPR2 as a novel component involved in cell kill provoked by cisplatin and doxorubicin, and our data support the hypothesis that NPR2 and SKY1 may use mutual regulatory routes to mediate the cytotoxicity of these anticancer drugs.

Deletion of chromosomal region 6q14-16 in prostate cancer.

A detailed analysis of chromosome 6 in DNAs from prostate cancers was performed, to define a region for subsequent search for cancer genes. DNA from 4 prostate cancer cell lines and 11 xenografts was used for CGH and whole-chromosome allelotyping with polymorphic microsatellite markers. Loss of proximal 6q was studied in more detail by high-density allelotyping of xenografts, cell lines and 19 prostate tumour specimens from TURP. Seven of 15 xenografts and cell lines showed deletion of proximal 6q by CGH. Gain of 6q was found in 2 samples. Six samples showed 6p gain, and 1 had 6p loss. Allelotyping results were consistent with CGH data in 11 of 15 DNAs. In LNCaP and DU145 cells, CGH showed 6p loss and 6q loss, respectively, but 2 allelic bands were detected for many polymorphic markers on these chromosome arms. These apparent discrepancies might be explained by aneuploidy. In cell line TSU, allelotyping demonstrated chromosome 6 deletion, which was not clearly detected by CGH, indicating loss of 1 copy of chromosome 6 followed by gain of the retained copy during progressive tumour growth. Loss of heterozygosity was detected in 9 of 19 TURP specimens. Combining all data, we found a common minimal region of loss at 6q14-16 with a length of 8.6 Mbp flanked by markers D6S1609 and D6S417. One hundred and twenty-three STSs, ESTs, genes and candidate genes mapping in this interval were used to screen xenografts and cell lines for HDs, but none was detected. In summary, chromosome region 6q14-16 was deleted in approximately 50% of the prostate cancer specimens analysed. The high percentage of loss underscores the importance of genes within this region in prostate cancer growth.

Inactivation of the Saccharomyces cerevisiae SKY1 gene induces a specific modification of the yeast anticancer drug sensitivity profile accompanied by a mutator phenotype.

The therapeutic potential of the highly active anticancer agent cisplatin is severely limited by the occurrence of cellular resistance. A better understanding of the molecular pathways involved in cisplatin-induced cell death could potentially indicate ways to overcome cellular unresponsiveness to the drug and thus lead to better treatment results. We used the budding yeast Saccharomyces cerevisiae as a model organism to identify and characterize novel genes involved in cisplatin-induced cell kill, and found that SKY1 (SR-protein-specific kinase from budding yeast) is a cisplatin sensitivity gene whose disruption conferred cisplatin resistance. In cross-resistance studies, we observed resistance of yeast sky1 Delta cells (i.e., cells from which the SKY1 gene had been disrupted) to cisplatin, carboplatin (but not oxaliplatin), doxorubicin and daunorubicin, and hypersensitivity to cadmium chloride and 5-fluorouracil. Furthermore, these cells did not display reduced platinum accumulation, DNA platination or doxorubicin accumulation, indicating that the resistance is unrelated to decreased drug import or increased drug export. Based on the modification of the anticancer drug sensitivity profile and our finding that sky1 Delta cells display a mutator phenotype, we propose that Sky1p might play a significant role in specific repair and/or tolerance pathways. Disruption of the S. cerevisiae SKY1 gene would thus result in deregulation of such mechanisms and, consequently, lead to altered drug sensitivity.