Transient Differentiation-State Plasticity Occurs during Acute Lymphoblastic Leukemia Initiation.

Leukemia is characterized by oncogenic lesions that result in a block of differentiation, whereas phenotypic plasticity is retained. A better understanding of how these two phenomena arise during leukemogenesis in humans could help inform diagnosis and treatment strategies. Here, we leveraged the well-defined differentiation states during T-cell development to pinpoint the initiation of T-cell acute lymphoblastic leukemia (T-ALL), an aggressive form of childhood leukemia, and study the emergence of phenotypic plasticity. Single-cell whole genome sequencing of leukemic blasts was combined with multiparameter flow cytometry to couple cell identity and clonal lineages. Irrespective of genetic events, leukemia-initiating cells altered their phenotypes by differentiation and dedifferentiation. The construction of the phylogenies of individual leukemias using somatic mutations revealed that phenotypic diversity is reflected by the clonal structure of cancer. The analysis also indicated that the acquired phenotypes are heritable and stable. Together, these results demonstrate a transient period of plasticity during leukemia initiation, where phenotypic switches seem unidirectional. Significance: A method merging multicolor flow cytometry with single-cell whole genome sequencing to couple cell identity with clonal lineages uncovers differentiation-state plasticity in leukemia, reconciling blocked differentiation with phenotypic plasticity in cancer.

Single-cell RNA sequencing of pediatric Hodgkin lymphoma to study the inhibition of T cell subtypes.

Pediatric classic Hodgkin lymphoma (cHL) patients have a high survival rate but suffer from severe long-term side effects induced by chemo- and radiotherapy. cHL tumors are characterized by the low fraction (0.1%-10%) of malignant Hodgkin and Reed-Sternberg (HRS) cells in the tumor. The HRS cells depend on the surrounding immune cells for survival and growth. This dependence is leveraged by current treatments that target the PD-1/PD-L1 axis in cHL tumors. The development of more targeted therapies that are specific for the tumor and are therefore less toxic for healthy tissue compared with conventional chemotherapy could improve the quality of life of pediatric cHL survivors. Here, we applied single-cell RNA sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. Besides TNFRSF8 (CD30), we identified other genes of cell surface proteins that are consistently overexpressed in HRS cells, such as NRXN3 and LRP8, which can potentially be used as alternative targets for antibody-drug conjugates or CAR T cells. Finally, we identified potential interactions by which HRS cells inhibit T cells, among which are the galectin-1/CD69 and HLA-II/LAG3 interactions. RNAscope was used to validate the enrichment of CD69 and LAG3 expression on T cells near HRS cells and indicated large variability of the interaction strength with the corresponding ligands between patients and between tumor tissue regions. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets, specifically those that target tumor-immune cell interactions.

Selective pressures of platinum compounds shape the evolution of therapy-related myeloid neoplasms.

Therapy-related myeloid neoplasms (t-MN) arise as a complication of chemo- and/or radiotherapy. Although t-MN can occur both in adult and childhood cancer survivors, the mechanisms driving therapy-related leukemogenesis likely vary across different ages. Chemotherapy is thought to induce driver mutations in children, whereas in adults pre-existing mutant clones are selected by the exposure. However, selective pressures induced by chemotherapy early in life are less well studied. Here, we use single-cell whole genome sequencing and phylogenetic inference to show that the founding cell of t-MN in children starts expanding after cessation of platinum exposure. In patients with Li-Fraumeni syndrome, characterized by a germline TP53 mutation, we find that the t-MN already expands during treatment, suggesting that platinum-induced growth inhibition is TP53-dependent. Our results demonstrate that germline aberrations can interact with treatment exposures in inducing t-MN, which is important for the development of more targeted, patient-specific treatment regimens and follow-up.

Improved detection of colibactin-induced mutations by genotoxic E. coli in organoids and colorectal cancer.

Co-culture of intestinal organoids with a colibactin-producing pks+E. coli strain (EcC) revealed mutational signatures also found in colorectal cancer (CRC). E. coli Nissle 1917 (EcN) remains a commonly used probiotic, despite harboring the pks operon and inducing double strand DNA breaks. We determine the mutagenicity of EcN and three CRC-derived pks+E. coli strains with an analytical framework based on sequence characteristic of colibactin-induced mutations. All strains, including EcN, display varying levels of mutagenic activity. Furthermore, a machine learning approach attributing individual mutations to colibactin reveals that patients with colibactin-induced mutations are diagnosed at a younger age and that colibactin can induce a specific APC mutation. These approaches allow the sensitive detection of colibactin-induced mutations in ∼12% of CRC genomes and even in whole exome sequencing data, representing a crucial step toward pinpointing the mutagenic activity of distinct pks+E. coli strains.

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox.

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.