Reversible transitions between noradrenergic and mesenchymal tumor identities define cell plasticity in neuroblastoma.

Noradrenergic and mesenchymal identities have been characterized in neuroblastoma cell lines according to their epigenetic landscapes and core regulatory circuitries. However, their relationship and relative contribution in patient tumors remain poorly defined. We now document spontaneous and reversible plasticity between the two identities, associated with epigenetic reprogramming, in several neuroblastoma models. Interestingly, xenografts with cells from each identity eventually harbor a noradrenergic phenotype suggesting that the microenvironment provides a powerful pressure towards this phenotype. Accordingly, such a noradrenergic cell identity is systematically observed in single-cell RNA-seq of 18 tumor biopsies and 15 PDX models. Yet, a subpopulation of these noradrenergic tumor cells presents with mesenchymal features that are shared with plasticity models, indicating that the plasticity described in these models has relevance in neuroblastoma patients. This work therefore emphasizes that intrinsic plasticity properties of neuroblastoma cells are dependent upon external cues of the environment to drive cell identity.

Lipid-Associated Macrophages Are Induced by Cancer-Associated Fibroblasts and Mediate Immune Suppression in Breast Cancer.

Tumor-associated macrophages (TAM) play a detrimental role in triple-negative breast cancer (TNBC). In-depth analysis of TAM characteristics and interactions with stromal cells, such as cancer-associated fibroblast (CAF), could provide important biological and therapeutic insights. Here we identify at the single-cell level a monocyte-derived STAB1+TREM2high lipid-associated macrophage (LAM) subpopulation with immune suppressive capacities that is expanded in patients resistant to immune checkpoint blockade (ICB). Genetic depletion of this LAM subset in mice suppressed TNBC tumor growth. Flow cytometry and bulk RNA sequencing data demonstrated that coculture with TNBC-derived CAFs led to reprogramming of blood monocytes towards immune suppressive STAB1+TREM2high LAMs, which inhibit T-cell activation and proliferation. Cell-to-cell interaction modeling and assays in vitro demonstrated the role of the inflammatory CXCL12-CXCR4 axis in CAF-myeloid cell cross-talk and recruitment of monocytes in tumor sites. Altogether, these data suggest an inflammation model whereby monocytes recruited to the tumor via the CAF-driven CXCL12-CXCR4 axis acquire protumorigenic LAM capacities to support an immunosuppressive microenvironment. SIGNIFICANCE: This work identifies a novel lipid-associated macrophage subpopulation with immune suppressive functions, offering new leads for therapeutic interventions in triple-negative breast cancer.

Dichotomy in Neutralizing Antibody Induction to Peptide-Conjugated Vaccine in Squalene Emulsion Contrast With Aluminum Hydroxide Formulation.

W614A-3S peptide is a modified 3S motif of the HIV-gp41 (mutation W614A). We previously detected the presence of natural neutralizing antibodies directed against W614A-3S peptide (NAbs) in long-term non-progressor HIV+ patients. Here, we compared the efficacy of W614A-3S peptide formulated in either squalene emulsion (SQE) or in aluminum hydroxide (Alum) in inducing broadly-NAbs (bNAbs). Rabbit and mouse models were used to screen the induction of bNAbs following 4 immunizations. SQE was more efficient than Alum formulation in inducing W614A-3S-specific bNAbs with up to 67%-93% of HIV strains neutralized. We then analyzed the quality of peptide-specific murine B cells by single-cell gene expression by quantitative reverse transcription-PCR and single-cell V(D)J sequencing. We found more frequent germinal center B cells in SQE than in Alum, albeit with a different gene expression profile. The V(D)J sequencing of W614A-3S-specific BCR showed significant differences in BCR sequences and validates the dichotomy between adjuvant formulations. All sixteen BCR sequences which were cloned were specific of peptide. Adjuvant formulations of W614A-3S-peptide-conjugated immunogen impact the quantity and quality of B cell immune responses at both the gene expression level and BCR sequence.

DNMT3A-dependent DNA methylation is required for spermatogonial stem cells to commit to spermatogenesis.

DNA methylation plays a critical role in spermatogenesis, as evidenced by the male sterility of DNA methyltransferase (DNMT) mutant mice. Here, we report a division of labor in the establishment of the methylation landscape of male germ cells and its functions in spermatogenesis. Although DNMT3C is essential for preventing retrotransposons from interfering with meiosis, DNMT3A broadly methylates the genome (with the exception of DNMT3C-dependent retrotransposons) and controls spermatogonial stem cell (SSC) plasticity. By reconstructing developmental trajectories through single-cell RNA sequencing and profiling chromatin states, we found that Dnmt3A mutant SSCs can only self-renew and no longer differentiate in association with spurious enhancer activation that enforces an irreversible stem cell gene program. Our findings therefore highlight a key function of DNA methylation in male fertility: the epigenetic programming of SSC commitment to differentiation and lifelong spermatogenesis supply.

Kronos scRT: a uniform framework for single-cell replication timing analysis.

Mammalian genomes are replicated in a cell type-specific order and in coordination with transcription and chromatin organization. Currently, single-cell replication studies require individual processing of sorted cells, yielding a limited number (<100) of cells. Here, we develop Kronos scRT, a software for single-cell Replication Timing (scRT) analysis. Kronos scRT does not require a specific platform or cell sorting, which allows investigating large datasets obtained from asynchronous cells. By applying our tool to published data as well as droplet-based single-cell whole-genome sequencing data generated in this study, we exploit scRT from thousands of cells for different mouse and human cell lines. Our results demonstrate that although genomic regions are frequently replicated around their population average RT, replication can occur stochastically throughout S phase. Altogether, Kronos scRT allows fast and comprehensive investigations of the RT programme at the single-cell resolution for both homogeneous and heterogeneous cell populations.

A high-throughput real-time PCR tissue-of-origin test to distinguish blood from lymphoblastoid cell line DNA for (epi)genomic studies.

Lymphoblastoid cell lines (LCLs) derive from blood infected in vitro by Epstein-Barr virus and were used in several genetic, transcriptomic and epigenomic studies. Although few changes were shown between LCL and blood genotypes (SNPs) validating their use in genetics, more were highlighted for other genomic features and/or in their transcriptome and epigenome. This could render them less appropriate for these studies, notably when blood DNA could still be available. Here we developed a simple, high-throughput and cost-effective real-time PCR approach allowing to distinguish blood from LCL DNA samples based on the presence of EBV relative load and rearranged T-cell receptors γ and ß. Our approach was able to achieve 98.5% sensitivity and 100% specificity on DNA of known origin (458 blood and 316 LCL DNA). It was further applied to 1957 DNA samples from the CEPH Aging cohort comprising DNA of uncertain origin, identifying 784 blood and 1016 LCL DNA. A subset of these DNA was further analyzed with an epigenetic clock indicating that DNA extracted from blood should be preferred to LCL for DNA methylation-based age prediction analysis. Our approach could thereby be a powerful tool to ascertain the origin of DNA in old collections prior to (epi)genomic studies.

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.

Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41-4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19-65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).

Low temperature isothermal amplification of microsatellites drastically reduces stutter artifact formation and improves microsatellite instability detection in cancer.

Microsatellites are polymorphic short tandem repeats of 1-6 nucleotides ubiquitously present in the genome that are extensively used in living organisms as genetic markers and in oncology to detect microsatellite instability (MSI). While the standard analysis method of microsatellites is based on PCR followed by capillary electrophoresis, it generates undesirable frameshift products known as 'stutter peaks' caused by the polymerase slippage that can greatly complicate the analysis and interpretation of the data. Here we present an easy multiplexable approach replacing PCR that is based on low temperature isothermal amplification using recombinase polymerase amplification (LT-RPA) that drastically reduces and sometimes completely abolishes the formation of stutter artifacts, thus greatly simplifying the calling of the alleles. Using HT17, a mononucleotide DNA repeat that was previously proposed as an optimal marker to detect MSI in tumor DNA, we showed that LT-RPA improves the limit of detection of MSI compared to PCR up to four times, notably for small deletions, and simplifies the identification of the mutant alleles. It was successfully applied to clinical colorectal cancer samples and enabled detection of MSI. This easy-to-handle, rapid and cost-effective approach may deeply improve the analysis of microsatellites in several biological and clinical applications.

Evaluation of six blood-based age prediction models using DNA methylation analysis by pyrosequencing.

DNA methylation has been identified as the most promising molecular biomarker for the prediction of age. Several DNA methylation-based models have been proposed for age prediction based on blood samples, using mainly pyrosequencing. These methods present different performances for age prediction and have rarely, if ever, been evaluated and intercompared in an independent validation study. Here, for the first time, we evaluate and compare six blood-based age prediction models (Bekaert1, Park2, Thong3, Weidner4, and the Zbiec-Piekarska 15 and Zbiec-Piekarska 26), using DNA methylation analysis by pyrosequencing on 100 blood samples from French individuals aged between 19-65 years. For each model, we perform correlation analysis and evaluate age-prediction performance (mean absolute deviation (MAD) and standard error of the estimate (SEE)). The best age-prediction performances were found with the Bekaert and Thong models (MAD of 4.5-5.2, SEE of 6.8-7.2), followed by the Zbiec-Piekarska 1 model (MAD of 6.8 and SEE of 9.2), while the Park, Weidner and Zbiec-Piekarska 2 models presented lower performances (MAD of 7.2-8.7 and SEE of 9.2-10.3). Given these results, we recommend performing systematic, independent evaluation of all age prediction models on a same cohort to validate the different models and compare their performance.

Molecular and Computational Methods for the Detection of Microsatellite Instability in Cancer.

Microsatellite instability (MSI) is a genomic alteration in which microsatellites, usually of one to four nucleotide repeats, accumulate mutations corresponding to deletions/insertions of a few nucleotides. The MSI phenotype has been extensively characterized in colorectal cancer and is due to a deficiency of the DNA mismatch repair system. MSI has recently been shown to be present in most types of cancer with variable frequencies (from <1 to 30%). It correlates positively to survival outcome and predicts the response to immune checkpoint blockade therapy. The different methods developed for MSI detection in cancer require taking into consideration two critical parameters which influence method performance. First, the microsatellite markers used should be chosen carefully to ensure they are highly sensitive and specific for MSI detection. Second, the analytical method used should be highly resolute to allow clear identification of MSI and of the mutant allele genotype, and should present the lowest limit of detection possible for application in samples with low mutant allele frequency. In this review, we describe all the different molecular and computational methods developed to date for the detection of MSI in cancer, how they have evolved and improved over the years, and their advantages and drawbacks.