Hematopoietic stem cells (HSCs), reside in a specialized bone marrow (BM) microenvironment known as the hematopoietic stem niche. Despite the critical role of the niche in tightly controlling the ...processes of normal and malignant hematopoiesis, its cellular composition remains only partially understood. Recent studies, including our own, using single-cell RNA sequencing (scRNA-seq) approaches have provided valuable insights into the profiling of the human BM niche. However, a comprehensive effort to describe the cellular heterogeneity and regulatory circuitry of the aged BM microenvironment in elderly humans is still lacking. As individual age, multiple systems and organs experience a progressive loss of anatomical and physiological integrity. Aging of the HSC niche is accompanied by a reduction in the numbers and function of its constituents and a decrease in the levels of HSC-supporting factors. Whether niche aging can contribute to the defects observed in aged hematopoiesis, such as the clonal shift towards myelopoiesis, the decrease in immune surveillance, or age-associated metabolic diseases, remains unresolved. To address this, we utilized scRNA-seq and spatial transcriptomics to provide a detailed characterization of the molecular landscape and stromal interactions in the aged non-immune BM microenvironment. First, we performed scRNA-seq profiling on fluorescence-activated cell sorting-purified endothelial cells (ECs, TO-PRO-3 -/CD45 -/CD235 -/Lin -/CD31 +/CD9 +) and mesenchymal stromal cells (MSCs, TO-PRO-3 -/CD45 -/CD235 -/Lin -/CD271 +) from human BM samples of young (n=4) and elderly healthy donors (n=5). We analyzed a total of 1514 ECs and 3848 MSCs from older adults, grouped into 7 and 10 subclusters, respectively, defining distinct functional cell states. ECs and MSCs cells from young individuals were annotated using SingleR, utilizing the gene signature of each functional state in the elderly as a reference. Our results revealed significant shifts in the distribution of the functional states of BM niche cells during aging. Regarding ECs, we noticed reduced pathways associated with the cell cycle and RNA transcription pathways, indicating impaired cell cycle activity, coupled with decreased antioxidant defense (Figure 1A). In contrast, there was an increase in subgroups related to the response to foreign molecules, immune system activation, and vascular remodeling, suggesting an inflammatory response and increased vascular remodeling processes associated with aging. For MSCs, we observed a decline in osteogenesis and a reduction in the proportion of the early mesenchymal group related to immunity and the extracellular matrix (Figure 1B). These changes could contribute to the decreased ability of MSCs in elderly individuals to maintain HSCs function. On the contrary, we noticed increased adipogenic differentiation to the detriment of osteogenesis, which could be responsible for osteoporosis problems. Next, and to further explore the location and the direct interactions between niche cells, we are currently integrating spatially resolved transcriptomics with our scRNA-seq data to accurately comprehend the spatial distribution and interactions among the BM niche cells, using for the first time 10x Genomics Visium Spatial Gene Expression on bone BM tissue in humans. As a final validation step, we are using a mouse model to validate further the mechanisms of age-associated changes in the BM microenvironment. In summary, our results provide valuable insights into age-related transcriptional alterations in human BM ECs and MSCs, suggesting altered behavior of these niche cells during the aging of the hematopoietic system. This deeper understanding of the architecture of the aged hematopoietic system and its microenvironment offers the potential for developing novel therapeutic strategies preventing the detrimental effects of aging.
Introduction:Despite recent advances in AML treatment, patients continue to relapse and become chemotherapy resistant, leading to poor long-term overall survival. The identification of this ...measurable residual disease (MRD), defined as the post-therapy presence of leukemic cells, currently stands as one of the most well-established risk factors. The abnormal phenotypic and molecular characteristics of AML cells offer an opportunity for disease monitoring using techniques like multiparameter flow cytometry (MFC) and qPCR, which are currently considered the gold standard for MRD detection. However, these techniques have limitations. The aim of this study was to validate a different approach using single-cell DNA sequencing (scDNAseq) technology to detect MRD in patients achieving complete response (CR) and to characterize the genomic landscape of MRD clones and the potential identification of clonal evolution. Methods:We selected 24 cryopreserved bone marrow samples from 15 AML patients who participated in the QUIWI-PETHEMA clinical trial (NCT04107727) and achieved CR after induction and consolidation (n=20). 4 diagnosis samples were analyzed to determine genomic differences between the MRD clone and the initial leukemic population. All patients had bulk targeted NGS data available at diagnosis. Selection of CD34+ and/or CD117+ cells was performed using magnetic beads for enrichment of blasts and Mission Bio multiome single cell DNA+protein was performed using an AML-related 469 amplicon panel and 19 surface antibody mix. Multiplex of 3 independent samples was performed in each library preparation. Analysis was done according to manufacturer's instructions. MRD was also analyzed using MFC (n=14) EuroFlow panel with a limit of detection of 0.1% aberrant cells. RNA qRT-PCR was used in cases with NPM1 mutations (n=6). Quantification of MRD by scDNAseq was calculated according to the enrichment performance obtained from the manufacturer and the percentage of mutant cells. Results: The concordance between gold standard techniques for MRD and scDNAseq was 75% (15/20) (Table 1). Concordance between MFC and scDNAseq was 78% (11/14). The 3 discordant cases, positives by scDNAseq, MRD levels ranged between 0.04-0.09%, below the consensus cutoff of 0.1% to define MRD+. These results suggest that scDNAseq may complement MFC in the detection of very low levels of MRD. Concordance with qRT-PCR was 66% (4/6), but we only detected one patient with a persistent NPM1 clone. Taking advantage of the single cell approach, we were able to assess the genomic landscape of MRD clones and the clonal evolution in sequential samples. The number of clones/subclones and the number of variants per clone varied between patients with positive MRD as shown in Table 1. Interestingly, we analyzed 4 samples at diagnosis by scDNAseq and observed 2 cases in which MRD mutation was already present at diagnosis but was not informed as VAF was < 1%. In 4 patients, we detected small clones (around 1%) that remained unchanged in size despite treatment, suggesting that they likely represent clonal hematopoiesis. In 6 cases, consecutive samples were obtained showing clearance of some clones with other ones remaining stable (UPN2), progressive clearance of clones (UPN3, UPN4), acquisition of new clones (UPN9) and clearance of some clones and acquisition of new ones (UPN15) (Figure 1). Integration of scDNA and cell surface protein expression in the same cell allowed us to perform mutation-clone specific immunophenotypic analysis. Some cases showed a clear pattern in which one of the mutant clones had a significantly higher expression of some markers that was correlated with previous flow cytometry data (e.g. UPN1). Conclusions: Our study suggests that the use of scDNA technology is a feasible approach for detection of MRD in AML patients. Moreover, the use of this approach in sequential samples may allow deciphering clonal evolution, the co-occurrence of different mutations including potential clonal hematopoiesis mutations and identifying winner clones potentially responsible for disease persistence and relapse. Finally, the integration of mutations and surface antibody markers in the same cell provides a means for identifying the presence of mutations in different cell populations. Validation of these results in larger series of patients and correlation with clinical outcome are the next steps for validation of this technology.
Multiple Myeloma (MM) is a malignant plasma cell (PC) disorder characterized by a heterogeneous distribution of PCs in the bone marrow (BM) where the interactions between the PCs and the BM ...microenvironment guide the pathogenesis of the disease. The development of single cell technologies has contributed to understand the transcriptional heterogeneity of the disease both from the tumor and the microenvironment point of view, yet the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. To address the role of spatially resolved interactions in MM, we performed spatial transcriptomic analysis in BM from the MI cγ1mice strain (Larrayoz et al Nat Med. 2023) a recently described mouse model that recapitulates the characteristics of a MYC driven human MM disease using the Visium Spatial Gene Expression analysis (10x Genomics). Using formalin-fixed paraffin-embedded (FFPE) BM tissues from the femur of control mice, we first characterized the healthy BM. Considering that each spot contains an averaged transcriptomic profile of 3-10 cells, we generated a single-cell reference set that included the most prevalent cell types in the BM to identify the cell type contribution per spot. The relative proportions of the estimations are consistent with percentage estimations observed by previous works (Hongzhe et al, eLife. 2023). Next, using the “cell proportion estimations per spot” we identified four different clusters of spots. A deeper characterization of those clusters revealed a positive correlation between erythroblasts and B cells, and a negative correlation between both cell types and neutrophils. Additionally, we spatially defined clusters 1 and 2, those with larger proportion of erythroblasts, in the metaphysis trabecular regions of the bone marrow. We followed the same analysis framework to characterize the spatial configuration in the MI cγ1 mice BM with a developed MM. To this end, we incorporated the MM-derived single-cell PCs in the single-cell reference set. Importantly, the pathological PCs were identified and organized in large groups in the BM space. Cell proportion estimations in these samples revealed a distribution in 7 clusters, 4 of them concentrated in the periphery of the PC hot spots and 3 mirroring the PC gradient observed in previous analysis (Figure 1A). We next performed a targeted differential analysis to confirm previous observed markers identities of different MM processes as Cd44 (de Jong et al, Nat Immunol. 2021), a signature of dormant cells (Khoo et al, Blood. 2019), the 38 MM-associated surface-protein-encoding genes (Yao et al, Cancer Res. 2023), Mmp9 and different profiles of T cell exhaustion markers within the 3 clusters with higher PC concentration. These analyses allowed us to verify two different markers, Cd44 and Mmp9 localized in the periphery of the hot spots of PC which may explain an invasive mechanism of the cells localized in the outer areas of the MM combining an inflammatory environment, manifested by a Cd44 increment, with a degradative mechanism driven by Mmp9. Simultaneously, an untargeted differential analysis aimed to identify markers characterizing the clusters with high PC prevalence, revealed novel marker genes never described before in MM and not associated with PC proportion, as the Transmembrane Immune Signaling Adaptor ( Tyrobp) in the cluster 5 (peripheral cluster), which is predictive of a poor prognosis and high tumor immune infiltration in other described tumors (Lu et al BMC Cancer 2021) (Fig 1B). Finally, as a proof of principle of this technology potential in human samples, spatial transcriptomic was applied to FFPE samples from BM biopsies of 7 MM patients with different degrees of PC infiltration, providing a source for validation of the results obtained in the mouse model. In conclusion, our findings demonstrate that the application of spatial transcriptomics represents a useful tool for understanding the spatial architecture and niche specific interactions in human diseases, offering a systemic approach to dissect the role of the spatial interactions in the pathogenesis of MM.
Background: The incidence of SPM in transplant eligible MM patients (pts) receiving lenalidomide maintenance is ≥ 12% and is associated with inferior overall survival (OS). Recent evidence suggests ...that while clonal hematopoiesis does not increase the risk of SPM, specific TP53 mutant HPC may expand under lenalidomide treatment and give rise to therapy related myeloid neoplasms and acute lymphoblastic leukemia. Genetic screening may facilitate personalized treatment to minimize the risk of SPM. However, there are no longitudinal studies in purified HPC to inform on the evolution of specific gene mutations and its association with clinical outcomes. Aim: Analyze the mutational landscape of HPC at diagnosis and throughout lenalidomide based regimens. Methods: This study included 335 pts: 43 with high risk smoldering MM, 223 transplant eligible and 69 ineligible active MM respectively enrolled in the CESAR, GEM2012MENOS/GEM2014MAIN and CLARIDEX clinical trials. Of the 335 pts analyzed at diagnosis, 60 were further investigated after induction, 30 at day 100 after autologous transplant (ASCT) and 47 during maintenance. Two or more studies were available throughout treatment in 36 pts. Fluorescence activated cell sorting of CD34+ HPC was performed in a total of 500 bone marrow aspirates. DNA was analyzed with a panel of 55 genes recurrently mutated in myeloid neoplasms. Sequencing depth was >1000x in 95% of nucleotides. Criteria to filter out included synonymous, intronic, invalid-transcript, 5'UTR, panel error and single nucleotide polymorphisms. The criteria to filter in was a AMP/ACMG classification of uncertain significance, likely pathogenic or pathogenic. Only the latter two were included in downstream analysis. Results: HPC from 184 of the 335 (55%) pts were mutated. The frequency in high-risk smoldering MM, transplant eligible and ineligible active MM was 46%, 26% and 35%, respectively. The genes more frequently mutated were DNMT3A (n=94, 52%), TP53 (n=29, 16%) and TET2 (n=28, 15%). The median variant allele frequency was 4.9, 7.5 and 7.0, respectively. In a pt-paired analysis between diagnosis and induction, 8 mutations were present in both time points, 25 became undetectable and 22 were acquired during treatment. The latter (eg, PPM1D and SF3B1) were observed in 14 of the 60 (23%) pts. In the 30 pts with paired samples at diagnosis and at day 100 after ASCT, 4 mutations were present in both time points, 48 became undetectable and only 3 were acquired during treatment ( ATRX, MPL and SAMDL9). Thus, the frequency of mutant HPC was higher at diagnosis vs ASCT (23% vs 5%, P <.001). In a pt-paired analysis between diagnosis and maintenance, 13 mutations were present in both time points, 12 became undetectable and 30 were acquired during treatment. The latter (eg, PPM1D and SF3B1) were observed in 24 of the 47 (51%) pts screened at both time points, and after a median of 5 years since diagnosis. With a median follow-up of 6 years, 17 of the 335 (5%) pts developed SPM. Mutant HPC were detected in 13 of the 17 pts. Accordingly, presence of mutant HPC was associated with a 2-fold increased risk of SPM (OR: 2.3; P = .03). Of the 13 pts, 3 showed mutations at diagnosis and in 8 these emerged during maintenance. The only case developing a myeloid neoplasm had a TP53 mutation present during maintenance that was undetectable at diagnosis. Pts with mutant vs non-mutated HPC at diagnosis showed similar OS (6y rates of 86% and 81%, respectively; P =.46). Similarly, there were no differences in OS of pts with emerging mutations vs those without mutant HPC after treatment (6y rates of 85% and 83%, respectively; P =.65). Specific mutations in DNMT3A, TP53 and TET2 and were not associated with inferior OS. Conclusions: To our knowledge this is the first study analyzing the mutational landscape of purified HPC throughout lenalidomide based regimens in high risk smoldering MM as well as transplant eligible and ineligible active MM. Deep sequencing of CD34+ HPC uncovered that the frequency of mutations is similar between precursor and malignant disease, and that TP53 is amongst the top mutated genes. There was considerable volatility with presence of both transient and emerging mutations throughout treatment. Importantly, the detection of mutant HPC was associated with increased risk of SPM without differences in survival. Thus, this study supports the longitudinal screening of HPC for the identification of patients at risk of developing SPM.
Risk of developing myelodysplastic syndrome (MDS) is significantly increased in both multiple myeloma (MM) and monoclonal gammopathy of undetermined significance, suggesting that it is therapy ...independent. However, the incidence and sequelae of dysplastic hematopoiesis at diagnosis are unknown. Here, we used multidimensional flow cytometry (MFC) to prospectively screen for the presence of MDS-associated phenotypic alterations (MDS-PA) in the bone marrow of 285 patients with MM enrolled in the PETHEMA/GEM2012MENOS65 trial (#NCT01916252). We investigated the clinical significance of monocytic MDS-PA in a larger series of 1252 patients enrolled in 4 PETHEMA/GEM protocols. At diagnosis, 33 (11.6%) of 285 cases displayed MDS-PA. Bulk and single-cell–targeted sequencing of MDS recurrently mutated genes in CD34+ progenitors (and dysplastic lineages) from 67 patients revealed clonal hematopoiesis in 13 (50%) of 26 cases with MDS-PA vs 9 (22%) of 41 without MDS-PA; TET2 and NRAS were the most frequently mutated genes. Dynamics of MDS-PA at diagnosis and after autologous transplant were evaluated in 86 of 285 patients and showed that in most cases (69 of 86 80%), MDS-PA either persisted or remained absent in patients with or without MDS-PA at diagnosis, respectively. Noteworthy, MDS-associated mutations infrequently emerged after high-dose therapy. Based on MFC profiling, patients with MDS-PA have altered hematopoiesis and T regulatory cell distribution in the tumor microenvironment. Importantly, the presence of monocytic MDS-PA at diagnosis anticipated greater risk of hematologic toxicity and was independently associated with inferior progression-free survival (hazard ratio, 1.5; P = .02) and overall survival (hazard ratio, 1.7; P = .01). This study reveals the biological and clinical significance of dysplastic hematopoiesis in newly diagnosed MM, which can be screened with moderate sensitivity using cost-effective MFC.
•Approximately 1 of 10 patients with MM displays MDS-associated phenotypic abnormalities at diagnosis and have inferior survival.•MDS-associated phenotypic abnormalities modify the tumor microenvironment and induce greater risk of hematologic toxicity from treatment.
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Background & Aims: Cl− /HCO3− anion exchanger 2 (AE2) is involved in intracellular pH (pHi ) regulation and transepithelial acid-base transport, including secretin-stimulated biliary bicarbonate ...excretion. AE2 gene expression was found to be reduced in liver biopsy specimens and blood mononuclear cells from patients with primary biliary cirrhosis (PBC), a disease characterized by chronic nonsuppurative cholangitis associated with antimitochondrial antibodies (AMA) and other autoimmune phenomena. In mice with widespread Ae2 gene disruption, we previously reported altered spermiogenesis and reduced gastric acid secretion. We now describe the hepatobiliary and immunologic changes observed in these Ae2a.b -deficient mice. Methods: In this murine model, splenocyte pHi and T-cell populations were studied by flow cytometry. CD3-stimulated cytokine secretion was estimated using cytokine arrays. AMA were evaluated by immunoblotting and proteomics. Hepatobiliary changes were assessed by immunohistopathology, flow cytometry, and serum biochemistry. Cholangiocyte gene expression was analyzed by real-time polymerase chain reaction. Results: Ae2a,b−/− mice exhibit splenomegaly, elevated pHi in splenocytes, increased production of interleukin-12p70 and interferon gamma, expanded CD8+ T-cell population, and under represented CD4+ FoxP3+ /regulatory T cells. Most Ae2a,b−/− mice tested positively for AMA, showing increased serum levels of immunoglobulin M and G, and liver-specific alkaline phosphatase. About one third of Ae2a,b−/− mice had extensive portal inflammation with CD8+ and CD4+ T lymphocytes surrounding damaged bile ducts. Cholangiocytes isolated from Ae2a,b−/− mice showed gene expression changes compatible with oxidative stress and increased antigen presentation. Conclusions: Ae2 deficiency alters pHi homeostasis in immunocytes and gene expression profile in cholangiocytes, leading to immunologic and hepatobiliary changes that resemble PBC.
Background: Clonal evolution in AML originates long before diagnosis and is a highly dynamic process. Having a greater understanding of leukemogenesis may contribute to develop treatment strategies ...that target the tumor evolutionary process. However, dissecting leukemic transformation at the onset of AML is challenging without single-cell sequencing, and most clinical laboratories do not have infrastructure to perform these studies routinely.
Patients with newly diagnosed AML may present dysplasia. If these residual, mature, dysplastic cells were generated before the differentiation blockage of blasts preceding leukemic transformation, it could be hypothesized that studying the genetic landscape of dysplastic cells and blasts could uncover the evolutionary process from dysplasia to AML. This hypothesis has never been investigated.
Aim: Reconstruct clonal evolution from dysplasia to AML based on the genetic signature of dysplastic cells and leukemic blasts, analyzed using integrated MFC immunophenotyping and sorting with NGS.
Methods: Presence of dysplasia according to aberrant phenotypic differentiation of the neutrophil, monocytic and erythroid lineages was investigated using MFC and EuroFlow MDS/AML panels in 283 newly diagnosed AML patients (median age 74; range 29-90). Patient-specific phenotypes were leveraged to isolate a total of 99 cell types from 22 AML cases for targeted (48 MDS/AML related genes) and whole-exome sequencing (WES), with a mean depth of 3246x and 141x, respectively. In patients with measurable residual disease (MRD) by MFC at the time of complete remission, tumor resistant cells were FACSorted for WES using patient-specific aberrant phenotypes. T cells were used as germline control in both approaches. Mutations were considered if ≥0.05 allele frequency in leukemic blasts or dysplastic cells and ≤0.2 in T cells.
Results: We first assessed the applicability of our hypothesis by investigating how many patients show dysplasia at the onset of AML. Dysplastic cells were observed in 252 of 283 (89%) cases. Phenotypic abnormalities were more frequently noted in the neutrophil lineage (47%), followed by the monocytic (40%) and erythroid cells (13%). Up to 169/283 (60%) patients showed multi-lineage dysplasia. Only nine cases showed no signs of dysplasia, whereas the remaining 22 had undetectable hematopoiesis.
Targeted sequencing of dysplastic cells and blasts in 16 patients uncovered three evolutionary patterns of leukemogenesis. Stable transition in those displaying identical mutational landscapes in blasts and residual mature dysplastic cells (9/16); clonal selection in cases where blasts originated from leukemic stem cells other than the ones driving dysplasia, due to mutations absent in blasts and present in dysplastic cells (4/16); and clonal evolution in cases showing new mutations in blasts onto mutations shared between these and dysplastic cells (3/16). Interestingly, most patients displaying stable transition from dysplasia to AML had mutated ASXL1, RUNX1 and/or TP53 (8/9). Mutations present in dysplastic cells while absent in blasts from patients showing a clonal selection evolutionary pattern, were more frequently detected in genes related to signaling pathways (eg JAK2, KRAS and NRAS). By contrast, clonal evolution was characterized by new mutations affecting FLT3ITD and STAG2.
The higher throughput of WES of dysplastic cells and blasts from six patients unveiled a more complex dynamic process of leukemogenesis, with all three evolutionary patterns being detectable in nearly all cases. Most interestingly, we found patients with mutations in dysplastic cells and blasts at diagnosis, but not in MRD cells (eg NBPF1 and ZNF717); and patients showing mutations in dysplastic and MRD cells, but not in blasts at diagnosis (eg MUC2 and KIR2DL3). These findings uncover that genetic alterations that are critical in leukemic transformation and chemoresistance, may not overlap (Figure).
Conclusions: We showed for the first time that it is possible to reconstruct leukemogenesis in nearly 90% of newly-diagnosed AML patients, using techniques that are commonly available in clinical laboratories. The possibility to identify the genetic drivers of leukemic transformation and chemoresistance, could be clinically meaningful to develop tailored treatment strategies aiming at the eradication of genetically diverse leukemic clones.
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Prósper: Oryzon: Honoraria; Janssen: Honoraria; BMS-Celgene: Honoraria, Research Funding. Ayala: Incyte Corporation: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas: Honoraria; Celgene: Honoraria. Perez-Simon: JANSSEN, TAKEDA, PFIZER, JAZZ, BMS, AMGEN, GILEAD: Other: honorarium or budget for research projects and/or participation in advisory boards and / or learning activities and / or conferences. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Montesinos: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Stemline/Menarini: Consultancy; Teva: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Agios: Consultancy; Tolero Pharmaceutical: Consultancy; Forma Therapeutics: Consultancy; Glycomimetics: Consultancy; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astellas Pharma, Inc.: Consultancy, Honoraria, Other: Advisory board, Research Funding, Speakers Bureau. Paiva: Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy.
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