Background: The development of methylation array platforms has allowed large scale studies on cancer epigenomes. Apart from intended analyses on methylation patterns, it is also possible to infer copy number profiles by leveraging the signal from methylation array data. To disentangle complex mixtures of phylogenetically related clones, it is best to jointly analyze different samples (different regions, timepoints, etc.) from the same tumor. However, current methods for studying copy number aberrations (CNAs) from methylation arrays consider tumor samples independently. In this project, we introduce Multi-Sample EPIC Phylogenetic Reconstruction (MultiSEPhyR), aiming to investigate the copy number profiles and clonal compositions from multi-sample methylation array data. Material and methods: As part of the GCGR (Glioma Cellular Genetic Resource; gcgr.org.uk) project, we analyze 53 samples from 26 cases with multiple methylation array data of primary glioblastomas, tumor-derived cell lines and xenograft re-derived cell lines. Copy Number Aberrations (CNAs) called from the methylation array data are validated using WGS data from a subset of the cohort. By jointly clustering the segmented LogR ratios from related samples, we can define tumor clones based on clustered CNA events. We use a two-step approach, where we firstly identify clonal events to obtain sample purity and tumor ploidy and use these values to subsequently infer the copy number state and the clonality of the remaining events. Results and Discussions: On a simulated dataset, MultiSEPhyR could accurately estimate sample purity and identify both clonal and sub-clonal CNA events. We then apply our method on GCGR dataset and show similar extent of intra-tumor heterogeneity in primary glioblastomas and derived cell lines. We also investigate clonal dynamics in each case. In the cell lines, while the heterogeneity is well captured, some sub-clonal CNA events may exhibit significantly different clonality compared to the primary glioblastomas. For example, we observe a clonal expansion of the clones harboring a deletion in chromosome 6 in xenograft re-derived cell lines. Conclusion We present a systematic way to call CNAs and resolve clonal compositions from methylation array data, leading to a cost-efficient way to study tumor evolution. Citation Format: Chuling Ding, Javier Herrero. Inferring phylogenetic trees based on copy number aberrations from methylation array [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A015.

Comparison of intratumor genetic heterogeneity in cancer at diagnosis and relapse suggests that chemotherapy induces bottleneck selection of subclonal genotypes. However, evolutionary events subsequent to chemotherapy could also explain changes in clonal dominance seen at relapse. We therefore investigated the mechanisms of selection in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) during induction chemotherapy where maximal cytoreduction occurs. To distinguish stochastic versus deterministic events, individual leukemias were transplanted into multiple xenografts and chemotherapy administered. Analyses of the immediate post-treatment leukemic residuum at single-cell resolution revealed that chemotherapy has little impact on genetic heterogeneity. Rather, it acts on extensive, previously unappreciated, transcriptional and epigenetic heterogeneity in BCP-ALL, dramatically reducing the spectrum of cell states represented, leaving a genetically polyclonal but phenotypically uniform population, with hallmark signatures relating to developmental stage, cell cycle and metabolism. Hence, canalization of the cell state accounts for a significant component of bottleneck selection during induction chemotherapy. Enver and colleagues report that epigenetic cell state, rather than genetic diversity, drives bottleneck selection of subclonal genotypes during induction chemotherapy in childhood B-cell precursor acute lymphoblastic leukemia.

Objectives To examine the characteristics and distribution of possible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target cells in the human trophectoderm (TE) and placenta. Methods Bioinformatics analysis was performed based on published single-cell transcriptomic datasets of early TE and first- and second-trimester human placentae. We conducted the transcriptomic analysis of 4198 early TE cells, 1260 first-trimester placental cells and 189 extra-villous trophoblast cells (EVTs) from 24-week placentae (EVT_24W) using the SMART-Seq2 method. In addition, to confirm the bioinformatic results, we performed immunohistochemical staining of three first-trimester, three second-trimester and three third-trimester placentae from nine women recruited prospectively to this study. We evaluated the expression of the SARS-CoV-2-related molecules angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2). Results Via bioinformatic analysis, we identified the existence of ACE2 and TMPRSS2 expression in human TE as well as in first- and second-trimester placentae. In the human TE, 54.4% of TE1 cells, 9.0% of cytotrophoblasts (CTBs), 3.2% of EVTs and 29.5% of syncytiotrophoblasts (STBs) were ACE2-positive. In addition, 90.7% of TE1 cells, 31.5% of CTBs, 22.1% of EVTs and 70.8% of STBs were TMPRSS2-positive. In placental cells, 20.4% of CTBs, 44.1% of STBs, 3.4% of EVTs from 8-week placentae (EVT 8W) and 63% of EVT_24W were ACE2-positive, while 1.6% of CTBs, 26.5% of STBs, 1.9% of EVT 8W and 20.1% of EVT_24W were TMPRSS2-positive. Pathway analysis revealed that EVT_24 W cells that were positive for both ACE2 and TMPRSS2 (ACE2 + TMPRSS2-positive) were associated with morphogenesis of branching structure, extracellular matrix interaction, oxygen binding and antioxidant activity. The ACE2 + TMPRSS2-positive TE1 cells were correlated with an increased capacity for viral invasion, epithelial-cell proliferation and cell adhesion. Expression of ACE2 and TMPRSS2 was observed on immunohistochemical staining in first-, second- and third-trimester placentae. Conclusions ACE2- and TMPRSS2-positive cells are present in the human TE and placenta in all three trimesters of pregnancy, which indicates the possibility that SARS-CoV-2 could spread via the placenta and cause intrauterine fetal infection. (C) 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Carbapenem resistant Klebsiella pneumoniae (CRKP) increasingly cause high-mortality outbreaks in hospital settings globally. Following a patient fatality at a hospital in Beijing due to a bla(KPC-2)-positive CRKP infection, close monitoring was put in place over the course of 14 months to characterize all bla(KPC-2)-positive CRKP in circulation in the hospital. Whole genome sequences were generated for 100 isolates from bla(KPC-2)-positive isolates from infected patients, carriers and the hospital environment. Phylogenetic analyses identified a closely related cluster of 82 sequence type 11 (ST11) isolates circulating in the hospital for at least a year prior to admission of the index patient. The majority of inferred transmissions for these isolates involved patients in intensive care units. Whilst the 82 ST11 isolates collected during the surveillance effort all had closely related chromosomes, we observed extensive diversity in their antimicrobial resistance (AMR) phenotypes. We were able to reconstruct the major genomic changes underpinning this variation in AMR profiles, including multiple gains and losses of entire plasmids and recombination events between plasmids, including transposition of bla(KPC-2). We also identified specific cases where variation in plasmid copy number correlated with the level of phenotypic resistance to drugs, suggesting that the number of resistance elements carried by a strain may play a role in determining the level of AMR. Our findings highlight the epidemiological value of whole genome sequencing for investigating multi-drug-resistant hospital infections and illustrate that standard typing schemes cannot capture the extraordinarily fast genome evolution of CRKP isolates.