Chromatin mapping and single-cell immune profiling define the temporal dynamics of ibrutinib response in CLL

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for patients with chronic lymphocytic leukemia (CLL), despite extensive heterogeneity in this disease. To define the underlining regulatory dynamics, we analyze high-resolution time courses of ibrutinib treatment in patients with CLL, combining immune-phenotyping, single-cell transcriptome profiling, and chromatin mapping. We identify a consistent regulatory program starting with a sharp decrease of NF-kappa B binding in CLL cells, which is followed by reduced activity of lineage-defining transcription factors, erosion of CLL cell identity, and acquisition of a quiescence-like gene signature. We observe patient-to-patient variation in the speed of execution of this program, which we exploit to predict patient-specific dynamics in the response to ibrutinib based on the pre-treatment patient samples. In aggregate, our study describes time-dependent cellular, molecular, and regulatory effects for therapeutic inhibition of B cell receptor signaling in CLL, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring

Guadecitabine plus ipilimumab in unresectable melanoma: the NIBIT-M4 clinical trial

Purpose: The immuno-modulatory activity of DNA hypomethylating agents (DHA) suggests they may improve the effectiveness of cancer immunotherapies. The phase 1b NIBIT-M4 trial tested this hypothesis using the next-generation DHA guadecitabine combined with ipilimumab. Experimental Design: Unresectable Stage III/IV melanoma patients received escalating doses of guadecitabine 30, 45 or 60 mg/m2/day subcutaneously on Days 1-5 every 3 weeks, and ipilimumab 3 mg/kg intravenously on Day 1 every 3 weeks, starting 1 week after guadecitabine, for 4 cycles. Primary endpoints were safety, tolerability and maximum tolerated dose of treatment; secondary were immune-related (ir) disease control rate (DCR) and objective response rate (ORR); exploratory were changes in methylome, transcriptome, and immune contextures in sequential tumor biopsies, and pharmacokinetics. Results: Nineteen patients were treated; 84% had grade 3/4 adverse events, neither dose limiting toxicities per protocol nor overlapping toxicities were observed. Ir-DCR and ir-ORR were 42% and 26%, respectively. Median CpG site methylation of tumor samples (n=8) at Week 4 (74.5%) and Week 12 (75.5%) was significantly (p<0.05) lower than at baseline (80.3%), with a median of 2454 (Week 4) and 4131 (Week 12) differentially expressed genes. Among the 136 pathways significantly (p<0.05; Z score >2 or <-2) modulated by treatment, the most frequently activated were immune-related. Tumor immune contexture analysis (n=11) demonstrated up-regulation of HLA class I on melanoma cells, an increase in CD8+, PD-1+ T cells and in CD20+ B cells in post-treatment tumor cores. Conclusions: Treatment of guadecitabine combined with ipilimumab is safe and tolerable in advanced melanoma, and has promising immunomodulatory and anti-tumour activity. Copyright ©2019, American Association for Cancer Research

Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species

DNA methylation is involved in regulatory processes throughout the animal kingdom. Here, the authors map DNA methylation in 535 vertebrates and 45 invertebrates, establishing a reference dataset for cross-species analysis and exploring epigenetic variation across vertebrate evolution

Additional file 6 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 6. Supplementary Table 6. Top GO Biological Processes, GO Cellular Components, GO Molecular Functions, Reactome, and KEGG Pathways enriched from significantly differentially methylated regions (FDR 0.075) identified when overlapping DMRs identified in the main analysis with DMRs identified when samples were limited to participants aged 50 and above at recruitment

Additional file 1 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 1. Supplementary Methods, Supplementary Tables and References

Additional file 7 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 7: Fig. S2. Relative proportions of hypermethylated, hypomethylated and all regions of the dataset when annotated by Enhancer status as annotated in the FANTOM5 enhancer atlas for the GM12878 human lymphoblastoid cell line; andgenic annotations

Additional file 2 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 2: Fig. S1. Distribution of participants within the model development and held-out sample sets byage at recruitment,body mass index,exit age, and proportion-of-whole graphs illustrating the distribution of participants bytumour subtype,menopausal status at recruitment,hormonal contraceptive use,hormone therapy use, andpregnancy history

Additional file 9 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 9. Supplementary Table 9. Genomic regions utilized by the PAM prediction model

Additional file 8 of Buffy coat signatures of breast cancer risk in a prospective cohort study

Additional file 8. Supplementary Table 7. Genomic regions in which DNA methylation is significantly correlated to length of time to diagnosis (days) by Kendall rank correlation (FDR < 0.05)