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Christoph Plass and colleagues investigate the transcriptomic and epigenomic changes induced by treatment with inhibitors of DNMT and HDAC in cancer cell lines. They observe large numbers of treatment-induced non-annotated TSSs (TINATs) encoded in long-terminal repeats that are normally repressed in most cell types. Several mechanisms of action have been proposed for DNA methyltransferase and histone deacetylase inhibitors (DNMTi and HDACi), primarily based on candidate-gene approaches. However, less is known about their genome-wide transcriptional and epigenomic consequences. By mapping global transcription start site (TSS) and chromatin dynamics, we observed the cryptic transcription of thousands of treatment-induced non-annotated TSSs (TINATs) following DNMTi and HDACi treatment. The resulting transcripts frequently splice into protein-coding exons and encode truncated or chimeric ORFs translated into products with predicted abnormal or immunogenic functions. TINAT transcription after DNMTi treatment coincided with DNA hypomethylation and gain of classical promoter histone marks, while HDACi specifically induced a subset of TINATs in association with H2AK9ac, H3K14ac, and H3K23ac. Despite this mechanistic difference, both inhibitors convergently induced transcription from identical sites, as we found TINATs to be encoded in solitary long terminal repeats of the ERV9/LTR12 family, which are epigenetically repressed in virtually all normal cells.

Christoph Plass, Christopher Oakes and colleagues study genome-wide DNA methylation dynamics during B cell maturation and the pathogenic role of transcription factor dysregulation in chronic lymphocytic leukemia (CLL). By comparing normal and malignant B cells, they find that tumors derive from a continuum of maturation states, which correlate with different clinical outcomes. Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes. We further uncovered that most previously reported tumor-specific methylation events are normally present in non-malignant B cells. Instead, we identified a potential pathogenic role for transcription factor dysregulation in CLL, where excess programming by EGR and NFAT with reduced EBF and AP-1 programming imbalances the normal B cell epigenetic program.

Cancer development is an evolutionary genomic process with parallels to Darwinian selection. It requires acquisition of multiple somatic mutations that collectively cause a malignant phenotype and continuous clonal evolution is often linked to tumor progression. Here, we show the clonal evolution structure in 15 myelofibrosis (MF) patients while receiving treatment with JAK inhibitors (mean follow-up 3.9 years). Whole-exome sequencing at multiple time points reveal acquisition of somatic mutations and copy number aberrations over time. While JAK inhibition therapy does not seem to create a clear evolutionary bottleneck, we observe a more complex clonal architecture over time, and appearance of unrelated clones. Disease progression associates with increased genetic heterogeneity and gain of RAS/RTK pathway mutations. Clonal diversity results in clone-specific expansion within different myeloid cell lineages. Single-cell genotyping of circulating CD34 + progenitor cells allows the reconstruction of MF phylogeny demonstrating loss of heterozygosity and parallel evolution as recurrent events. Myelofibrosis is a myeloproliferative neoplasm. Here, the authors show the clonal evolution of myelofibrosis during JAK inhibitor therapy, revealing how the treatment results in an increase in clonal complexity and a gain of RAS pathway mutations.

Fludarabine, cyclophosphamide, and rituximab (FCR) has become a gold-standard chemoimmunotherapy regimen for patients with chronic lymphocytic leukaemia. However, the question remains of how to treat treatment-naive patients with IGHV-unmutated chronic lymphocytic leukaemia. We therefore aimed to develop and validate a gene expression signature to identify which of these patients are likely to achieve durable remissions with FCR chemoimmunotherapy. We did a retrospective cohort study in two cohorts of treatment-naive patients (aged ≥18 years) with chronic lymphocytic leukaemia. The discovery and training cohort consisted of peripheral blood samples collected from patients treated at the University of Texas MD Anderson Cancer Center (Houston, TX, USA), who fulfilled the diagnostic criteria of the International Workshop on Chronic Lymphocytic Leukemia, had received at least three cycles of FCR chemoimmunotherapy, and had been treated between Oct 10, 2000, and Oct 26, 2006 (ie, the MDACC cohort). We did transcriptional profiling on samples obtained from the MDACC cohort to identify genes associated with time to progression. We did univariate Cox proportional hazards analyses and used significant genes to cluster IGHV-unmutated samples into two groups (intermediate prognosis and unfavourable prognosis). After using cross-validation to assess robustness, we applied the Lasso method to standardise the gene expression values to find a minimum gene signature. We validated this signature in an external cohort of treatment-naive patients with IGHV-unmutated chronic lymphocytic leukaemia enrolled on the CLL8 trial of the German Chronic Lymphocytic Leukaemia Study Group who were treated between July 21, 2003, and April 4, 2006 (ie, the CLL8 cohort). The MDACC cohort consisted of 101 patients and the CLL8 cohort consisted of 109 patients. Using the MDACC cohort, we identified and developed a 17-gene expression signature that distinguished IGHV-unmutated patients who were likely to achieve a long-term remission following front-line FCR chemoimmunotherapy from those who might benefit from alternative front-line regimens (hazard ratio 3·83, 95% CI 1·94–7·59; p<0·0001). We validated this gene signature in the CLL8 cohort; patients with an unfavourable prognosis versus those with an intermediate prognosis had a cause-specific hazard ratio of 1·90 (95% CI 1·18–3·06; p=0·008). Median time to progression was 39 months (IQR 22–69) for those with an unfavourable prognosis compared with 59 months (28–84) for those with an intermediate prognosis. We have developed a robust, reproducible 17-gene signature that identifies a subset of treatment-naive patients with IGHV-unmutated chronic lymphocytic leukaemia who might substantially benefit from treatment with FCR chemoimmunotherapy. We recommend testing the value of this gene signature in a prospective study that compares FCR treatment with newer alternative therapies as part of a randomised clinical trial. Chronic Lymphocytic Leukaemia Global Research Foundation and the National Institutes of Health/National Cancer Institute.

The maintenance of key germline derived DNA methylation patterns during preimplantation development depends on stores of DNA cytosine methyltransferase-1o (DNMT1o) provided by the oocyte. Dnmt1o(mat-/-) mouse embryos born to Dnmt1(Δ1o/Δ1o) female mice lack DNMT1o protein and have disrupted genomic imprinting and associated phenotypic abnormalities. Here, we describe additional female-specific morphological abnormalities and DNA hypomethylation defects outside imprinted loci, restricted to extraembryonic tissue. Compared to male offspring, the placentae of female offspring of Dnmt1(Δ1o/Δ1o) mothers displayed a higher incidence of genic and intergenic hypomethylation and more frequent and extreme placental dysmorphology. The majority of the affected loci were concentrated on the X chromosome and associated with aberrant biallelic expression, indicating that imprinted X-inactivation was perturbed. Hypomethylation of a key regulatory region of Xite within the X-inactivation center was present in female blastocysts shortly after the absence of methylation maintenance by DNMT1o at the 8-cell stage. The female preponderance of placental DNA hypomethylation associated with maternal DNMT1o deficiency provides evidence of additional roles beyond the maintenance of genomic imprints for DNA methylation events in the preimplantation embryo, including a role in imprinted X chromosome inactivation.

Radiotherapy is a fundamental part of cancer treatment but its use is limited by the onset of late adverse effects in the normal tissue, especially radiation-induced fibrosis. Since the molecular causes for fibrosis are largely unknown, we analyse if epigenetic regulation might explain inter-individual differences in fibrosis risk. DNA methylation profiling of dermal fibroblasts obtained from breast cancer patients prior to irradiation identifies differences associated with fibrosis. One region is characterized as a differentially methylated enhancer of diacylglycerol kinase alpha ( DGKA ). Decreased DNA methylation at this enhancer enables recruitment of the profibrotic transcription factor early growth response 1 (EGR1) and facilitates radiation-induced DGKA transcription in cells from patients later developing fibrosis. Conversely, inhibition of DGKA has pronounced effects on diacylglycerol-mediated lipid homeostasis and reduces profibrotic fibroblast activation. Collectively, DGKA is an epigenetically deregulated kinase involved in radiation response and may serve as a marker and therapeutic target for personalized radiotherapy. Radiotherapy can induce fibrosis in cancer patients, limiting its use in clinical settings. Here, the authors identify a differentially methylated enhancer of the lipid kinase DGKA in fibroblasts from breast cancer patients developing fibrosis after radiotherapy and they show that DGKA inhibition affects lipid homeostasis and reduces pro-fibrotic fibroblast activation.

Background Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging. Methods To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes. Results We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities. Conclusions Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

Epithelial growth factor-like 7 (EGFL7) is a protein that is secreted by endothelial cells and plays an important role in angiogenesis. Although EGFL7 is aberrantly overexpressed in solid tumors, its role in leukemia has not been evaluated. Here, we report that levels of both EGFL7 mRNA and EGFL7 protein are increased in blasts of patients with acute myeloid leukemia (AML) compared with normal bone marrow cells. High EGFL7 mRNA expression associates with lower complete remission rates, and shorter event-free and overall survival in older (age ≥60 y) and younger (age <60 y) patients with cytogenetically normal AML. We further show that AML blasts secrete EGFL7 protein and that higher levels of EGFL7 protein are found in the sera from AML patients than in sera from healthy controls. Treatment of patient AML blasts with recombinant EGFL7 in vitro leads to increases in leukemic blast cell growth and levels of phosphorylated AKT. EGFL7 blockade with an anti-EGFL7 antibody reduced the growth potential and viability of AML cells. Our findings demonstrate that increased EGFL7 expression and secretion is an autocrine mechanism supporting growth of leukemic blasts in patients with AML.

Background In cancer, normal epigenetic patterns are disturbed and contribute to gene expression changes, disease onset, and progression. The cancer epigenome is composed of the epigenetic patterns present in the tumor-initiating cell at the time of transformation, and the tumor-specific epigenetic alterations that are acquired during tumor initiation and progression. The precise dissection of these two components of the tumor epigenome will facilitate a better understanding of the biological mechanisms underlying malignant transformation. Chronic lymphocytic leukemia (CLL) originates from differentiating B cells, which undergo extensive epigenetic programming. This poses the challenge to precisely determine the epigenomic ground state of the cell-of-origin in order to identify CLL-specific epigenetic aberrations. Methods We developed a linear regression model, methylome-based cell-of-origin modeling (Methyl-COOM), to map the cell-of-origin for individual CLL patients based on the continuum of epigenomic changes during normal B cell differentiation. Results Methyl-COOM accurately maps the cell-of-origin of CLL and identifies CLL-specific aberrant DNA methylation events that are not confounded by physiologic epigenetic B cell programming. Furthermore, Methyl-COOM unmasks abnormal action of transcription factors, altered super-enhancer activities, and aberrant transcript expression in CLL. Among the aberrantly regulated transcripts were many genes that have previously been implicated in T cell biology. Flow cytometry analysis of these markers confirmed their aberrant expression on malignant B cells at the protein level. Conclusions Methyl-COOM analysis of CLL identified disease-specific aberrant gene regulation. The aberrantly expressed genes identified in this study might play a role in immune-evasion in CLL and might serve as novel targets for immunotherapy approaches. In summary, we propose a novel framework for in silico modeling of reference DNA methylomes and for the identification of cancer-specific epigenetic changes, a concept that can be broadly applied to other human malignancies.

Recently, a novel knowledge bank (KB) approach to predict outcomes of individual patients with acute myeloid leukemia (AML) was developed using unbiased machine learning. To validate its prognostic value, we analyzed 1612 adults with de novo AML treated on Cancer and Leukemia Group B front-line trials who had pretreatment clinical, cytogenetics, and mutation data on 81 leukemia/cancer-associated genes available. We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate the predictive values of the KB algorithm and other risk classifications. The KB algorithm predicted 3-year overall survival (OS) probability in the entire patient cohort (AUC KB  = 0.799), and both younger (< 60 years) (AUC KB  = 0.747) and older patients (AUC KB  = 0.770). The KB algorithm predicted non-remission death (AUC KB  = 0.860) well but was less accurate in predicting relapse death (AUC KB  = 0.695) and death in first complete remission (AUC KB  = 0.603). The KB algorithm’s 3-year OS predictive value was higher than that of the 2017 European LeukemiaNet (ELN) classification (AUC 2017ELN  = 0.707, p  < 0.001) and 2010 ELN classification (AUC 2010ELN  = 0.721, p  < 0.001) but did not differ significantly from that of the 17-gene stemness score (AUC 17-gene  = 0.732, p  = 0.10). Analysis of additional cytogenetic and molecular markers not included in the KB algorithm revealed that taking into account atypical complex karyotype, infrequent recurrent balanced chromosome rearrangements and mutational status of the SAMHD1 , AXL and NOTCH1 genes may improve the KB algorithm. We conclude that the KB algorithm has a high predictive value that is higher than those of the 2017 and 2010 ELN classifications. Inclusion of additional genetic features might refine the KB algorithm.