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Relapsed/refractory multiple myeloma (RRMM) is characterized by a remarkable heterogeneity and high drug resistance. Here, the authors analyse RRMM samples by single-cell RNA-sequencing, revealing molecular features associated with high-risk chromosomal 1q-gain and changes in the tumor microenvironment. Virtually all patients with multiple myeloma become unresponsive to treatment over time. Relapsed/refractory multiple myeloma (RRMM) is accompanied by the clonal evolution of myeloma cells with heterogeneous genomic aberrations and profound changes of the bone marrow microenvironment (BME). However, the molecular mechanisms that drive drug resistance remain elusive. Here, we analyze the heterogeneous tumor cell population and its complex interaction network with the BME of 20 RRMM patients by single cell RNA-sequencing before/after treatment. Subclones with chromosome 1q-gain express a specific transcriptomic signature and frequently expand during treatment. Furthermore, RRMM cells shape an immune suppressive BME by upregulation of inflammatory cytokines and close interaction with the myeloid compartment. It is characterized by the accumulation of PD1 + γδ T-cells and tumor-associated macrophages as well as the depletion of hematopoietic progenitors. Thus, our study resolves transcriptional features of subclones in RRMM and mechanisms of microenvironmental reprogramming with implications for clinical decision-making.

Deciphering Multiple Myeloma evolution in the whole bone marrow is key to inform curative strategies. Here, we perform spatial-longitudinal whole-exome sequencing, including 140 samples collected from 24 Multiple Myeloma patients during up to 14 years. Applying imaging-guided sampling we observe three evolutionary patterns, including relapse driven by a single-cell expansion, competing/co-existing sub-clones, and unique sub-clones at distinct locations. While we do not find the unique relapse sub-clone in the baseline focal lesion(s), we show a close phylogenetic relationship between baseline focal lesions and relapse disease, highlighting focal lesions as hotspots of tumor evolution. In patients with ≥3 focal lesions on positron-emission-tomography at diagnosis, relapse is driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion is typically seen ( p  < 0.01). Notably, we observe resistant sub-clones that can be hidden over years, suggesting that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy. Spatially and temporally resolved data can improve our understanding of evolution and treatment resistance in multiple myeloma (MM). Here, the authors analyse spatial and longitudinal heterogeneity in MM patients using multi-region sequencing, and identify subclones associated with relapse and therapy resistance.

In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression. The spatial architecture of multiple myeloma remains to be explored. Here, the authors perform bulk and single cell sequencing for samples from newly diagnosed patients and reveal gene signatures associated with focal lesions and spatial heterogeneity in the tumour microenvironment.

In chronic lymphocytic leukemia (CLL), a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF, as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF. CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B‐cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease. Synopsis Transcriptome profiling and genome‐scale mapping of DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, EBF1 and CTCF binding are performed in B cells from CLL patients and healthy donors. Altered chromatin features were detected at 80% of the differentially regulated genes in CLL and histone deacetylase activity was globally increased. Half of the CLL genome comprised partially DNA methylated domains that were transcriptionally downregulated, demarcated by CTCF and enriched for H3K9me3 and H3K27me3. H3K4me3 was redistributed at CLL promoters, including loss of bivalent H3K4me3/H3K27me3 states, and substantial changes of enhancer activity were detected. A gene regulatory network including enhancers was constructed around the transcription factors targeting 15 central binding motifs that were associated with aberrant CLL chromatin features. Genes involved in BCR signaling were enriched in the network. Graphical Abstract Transcriptome profiling and genome‐scale mapping of DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, EBF1 and CTCF binding are performed in B cells from CLL patients and healthy donors.

Mass spectrometry (MS) is a promising tool for monitoring monoclonal protein in plasma cell dyscrasias. We included 480 transplant-eligible newly-diagnosed multiple myeloma (MM) patients from the GMMG-MM5 trial (EudraCT No. 2010-019173-16) and performed a retrospective MS analysis at baseline (480 patients) and at the pre-defined, consecutive time points after induction (444 patients), prior to maintenance (305 patients) and after one year of maintenance (227 patients). We found that MS negativity was significantly associated with improved progression-free survival (PFS) even in patients with complete response (CR) at all investigated follow-up time points. The prognostic impact was independent of established risk factors, such as the revised International Staging System. Combining MS and baseline cytogenetics improved the prediction of outcome: MS-positive patients with high-risk cytogenetics had a dismal PFS of 1.9 years (95% confidence interval [CI]: 1.6–2.3 years) from the start of maintenance. Testing the value of sequential MS prior to and after one year of maintenance, patients converting from MS positivity to negativity had an excellent PFS (median not reached) while patients converting from MS negativity to positivity progressed early (median 0.6 years, 95% CI: 0.3-not reached). Among patients with sustained MS positivity, the baseline high-risk cytogenetic status had a significant impact and defined a group with poor PFS. Combining minimal residual disease (MRD) in the bone marrow and MS allowed the identification of double negative patients with a favorable PFS (median 3.33 years, 95% CI: 3.08-not reached) and no overall survival events. Our study provides strong evidence that MS is superior to conventional response monitoring, highlighting the potential of MS to become a new standard. Our data indicate that MS should be performed sequentially and combined with baseline disease features and MRD to improve its clinical value. Clinical Trials Register: EudraCT No. 2010-019173-16

Background Reactivation of the telomerase reverse transcriptase gene TERT is a central feature for unlimited proliferation of the majority of cancers. However, the underlying regulatory processes are only partly understood. Results We assembled regulator binding information from serveral sources to construct a generic human and mouse gene regulatory network. Advancing our “Mixed Integer linear Programming based Regulatory Interaction Predictor” (MIPRIP) approach, we identified the most common and cancer-type specific regulators of TERT across 19 different human cancers. The results were validated by using the well-known TERT regulation by the ETS1 transcription factor in a subset of melanomas with mutations in the TERT promoter. Our improved MIPRIP2 R-package and the associated generic regulatory networks are freely available at https://github.com/KoenigLabNM/MIPRIP . Conclusion MIPRIP 2.0 identified common as well as tumor type specific regulators of TERT . The software can be easily applied to transcriptome datasets to predict gene regulation for any gene and disease/condition under investigation.

The current risk stratification in prostate cancer (PCa) is frequently insufficient to adequately predict disease development and outcome. One hallmark of cancer is telomere maintenance. For telomere maintenance, PCa cells exclusively employ telomerase, making it essential for this cancer entity. However, TERT, the catalytic protein component of the reverse transcriptase telomerase, itself does not suit as a prognostic marker for prostate cancer as it is rather low expressed. We investigated if, instead of TERT, transcription factors regulating TERT may suit as prognostic markers. To identify transcription factors regulating TERT, we developed and applied a new gene regulatory modeling strategy to a comprehensive transcriptome dataset of 445 primary PCa. Six transcription factors were predicted as TERT regulators, and most prominently, the developmental morphogenic factor PITX1. PITX1 expression positively correlated with telomere staining intensity in PCa tumor samples. Functional assays and chromatin immune-precipitation showed that PITX1 activates TERT expression in PCa cells. Clinically, we observed that PITX1 is an excellent prognostic marker, as concluded from an analysis of more than 15,000 PCa samples. PITX1 expression in tumor samples associated with (i) increased Ki67 expression indicating increased tumor growth, (ii) a worse prognosis, and (iii) correlated with telomere length.

Multiple myeloma (MM) causes approximately 20% of deaths from blood cancers. Notwithstanding significant therapeutic progress, such as with proteasome inhibitors (PIs), MM remains incurable due to the development of resistance. mTORC1 is a key metabolic regulator, which frequently becomes dysregulated in cancer. While mTORC1 inhibitors reduce MM viability and synergize with other therapies in vitro, clinically, mTORC1 inhibitors are not effective for MM. Here we show that the inactivation of mTORC1 is an intrinsic response of MM to PI treatment. Genetically enforced hyperactivation of mTORC1 in MM was sufficient to compromise tumorigenicity in mice. In vitro, mTORC1-hyperactivated MM cells gained sensitivity to PIs and hypoxia. This was accompanied by increased mitochondrial stress and activation of the eIF2α kinase HRI, which initiates the integrated stress response. Deletion of HRI elevated the toxicity of PIs in wt and mTORC1-activated MM. Finally, we identified the drug PMA as a robust inducer of mTORC1 activity, which synergized with PIs in inducing MM cell death. These results help explain the clinical inefficacy of mTORC1 inhibitors in MM. Our data implicate mTORC1 induction and/or HRI inhibition as pharmacological strategies to enhance MM therapy by PIs.

The chromatin‐organizing factor CCCTC‐binding factor (CTCF) is involved in transcriptional regulation, DNA‐loop formation, and telomere maintenance. To evaluate the clinical impact of CTCF in prostate cancer, we analyzed CTCF expression by immunohistochemistry on a tissue microarray containing 17 747 prostate cancers. Normal prostate tissue showed negative to low CTCF expression, while in prostate cancers, CTCF expression was seen in 7726 of our 12 555 (61.5%) tumors and was considered low in 44.6% and high in 17% of cancers. Particularly, high CTCF expression was significantly associated with the presence of the transmembrane protease, serine 2:ETS‐related gene fusion: Only 10% of ERG‐negative cancers, but 30% of ERG‐positive cancers had high‐level CTCF expression (P < 0.0001). CTCF expression was significantly associated with advanced pathological tumor stage, high Gleason grade (P < 0.0001 each), nodal metastasis (P = 0.0122), and early biochemical recurrence (P < 0.0001). Multivariable modeling revealed that the prognostic impact of CTCF was independent from established presurgical parameters such as clinical stage and Gleason grade of the biopsy. Comparison with key molecular alterations showed strong associations with the expression of the Ki‐67 proliferation marker and presence of phosphatase and tensin homolog deletions (P < 0.0001 each). The results of our study identify CTCF expression as a candidate biomarker for prognosis assessment in prostate cancer. The transcriptional repressor CCCTC‐binding factor, which is involved in modeling the chromatin face in the nucleus of a cell, was analyzed for its expression in prostate cancer. We report here that its upregulation was associated with a shorter prostate‐specific antigen recurrence‐free survival after prostatectomy in a large cohort of prostate cancer patients.