Single-Cell Transcriptome Analysis Identifies Ligand-Receptor Pairs Associated With BCP-ALL Prognosis

Establishment and verification of a TME prognosis scoring model based on the acute myeloid leukemia single-cell transcriptome

The tumor microenvironment (TME) plays an important role in the occurrence and progression of Acute Myeloid Leukemia (AML). Single-cell sequencing has enabled researchers to explore the correlation between TME subgroups and tumor prognosis, distinguish the existence of drug-resistant subgroups of tumor cells, and unravel the complexity of the AML cellular heterogeneity. We used bone marrow immune cell enrichment analysis from public databases to screen prognostic genes, construct prognostic models, and validate their prognostic significance on independent external datasets and patient samples. A total of 18,251 single cells were obtained to establish prognostic scoring models for 10 key genes including CCL5, ETLS2, and IL2RA.The AML cases were divided into two groups: high-risk and low-risk. The low-risk group exhibited a higher survival rate than the high-risk group. The areas under curves (AUC) of 1-, 3- and 5-year survival curves in the TCGA and GEO training sets were greater than 0.8 and 0.6, respectively, indicating effective prediction. The model's prognostic efficacy was confirmed across multiple validation sets. It demonstrated increased expression of ETS2, CCL5, and IL2RA in AML samples compared to controls, which was associated with decreased overall survival (OS). This prognostic scoring model based on tumor immune infiltration provides a reference for developing novel treatment strategies for recurrent/refractory AML.

SINGLE CELL DISSECTION OF DEVELOPMENTAL ORIGINS AND TRANSCRIPTIONAL HETEROGENEITY IN B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA

Sequencing of bulk tumor populations has improved genetic classification and risk assessment of B-ALL, but does not directly examine intratumor heterogeneity or infer leukemia cellular origins. We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) and compared them to a reference map of normal human B-cell development established using both functional and molecular assays. Intra-sample heterogeneity was driven by cell cycle, metabolism, differentiation, and inflammation transcriptional programs. By inference of B lineage developmental state composition, nearly all samples possessed a high abundance of pro-B cells, with variation between samples mainly driven by sub-populations. However, ZNF384- r and DUX4- r B-ALL showed composition enrichment of hematopoietic stem cells, BCR::ABL1 and KMT2A -r ALL of Early Lymphoid progenitors, MEF2D -r and TCF3::PBX1 of Pre-B cells. Enrichment of Early Lymphoid progenitors correlated with high-risk clinical features. Understanding variation in transcriptional programs and developmental states of B-ALL by scRNA-seq refines existing clinical and genomic classifications and improves prediction of treatment outcome.

Single-cell analysis of acute lymphoblastic and lineage-ambiguous leukemia: approaches and molecular insights

Despite recent progress in identifying the genetic drivers of acute lymphoblastic leukemia (ALL), prognosis remains poor for those individuals who experience disease recurrence. Moreover, acute leukemias of ambiguous lineage lack a biologically informed framework to guide classification and therapy. These needs have driven the adoption of multiple complementary single-cell sequencing approaches to explore key issues in the biology of these leukemias, including cell of origin, developmental hierarchy and ontogeny, and the molecular heterogeneity driving pathogenesis, progression, and therapeutic responsiveness. There are multiple single-cell techniques for profiling a specific modality, including RNA, DNA, chromatin accessibility and methylation; and an expanding range of approaches for simultaneous analysis of multiple modalities. Single-cell sequencing approaches have also enabled characterization of cell-intrinsic and -extrinsic features of ALL biology. In this review we describe these approaches and highlight the extensive heterogeneity that underpins ALL gene expression, cellular differentiation, and clonal architecture throughout disease pathogenesis and treatment resistance. In addition, we discuss the importance of the dynamic interactions that occur between leukemia cells and the nonleukemia microenvironment. We discuss potential opportunities and limitations of single-cell sequencing for the study of ALL biology and treatment responsiveness.

Bone Marrow Stromal Cell Regeneration Profile in Treated B-Cell Precursor Acute Lymphoblastic Leukemia Patients: Association with MRD Status and Patient Outcome

For the last two decades, measurable residual disease (MRD) has become one of the most powerful independent prognostic factors in B-cell precursor acute lymphoblastic leukemia (BCP-ALL). However, the effect of therapy on the bone marrow (BM) microenvironment and its potential relationship with the MRD status and disease free survival (DFS) still remain to be investigated. Here we analyzed the distribution of mesenchymal stem cells (MSC) and endothelial cells (EC) in the BM of treated BCP-ALL patients, and its relationship with the BM MRD status and patient outcome. For this purpose, the BM MRD status and EC/MSC regeneration profile were analyzed by multiparameter flow cytometry (MFC) in 16 control BM (10 children; 6 adults) and 1204 BM samples from 347 children and 100 adult BCP-ALL patients studied at diagnosis (129 children; 100 adults) and follow-up (824 childhood samples; 151 adult samples). Patients were grouped into a discovery cohort (116 pediatric BCP-ALL patients; 338 samples) and two validation cohorts (74 pediatric BCP-ALL, 211 samples; and 74 adult BCP-ALL patients; 134 samples). Stromal cells (i.e., EC and MSC) were detected at relatively low frequencies in all control BM (16/16; 100%) and in most BCP-ALL follow-up samples (874/975; 90%), while they were undetected in BCP-ALL BM at diagnosis. In control BM samples, the overall percentage of EC plus MSC was higher in children than adults (p = 0.011), but with a similar EC/MSC ratio in both groups. According to the MRD status similar frequencies of both types of BM stromal cells were detected in BCP-ALL BM studied at different time points during the follow-up. Univariate analysis (including all relevant prognostic factors together with the percentage of stromal cells) performed in the discovery cohort was used to select covariates for a multivariate Cox regression model for predicting patient DFS. Of note, an increased percentage of EC (>32%) within the BCP-ALL BM stromal cell compartment at day +78 of therapy emerged as an independent unfavorable prognostic factor for DFS in childhood BCP-ALL in the discovery cohort—hazard ratio (95% confidence interval) of 2.50 (1−9.66); p = 0.05—together with the BM MRD status (p = 0.031). Further investigation of the predictive value of the combination of these two variables (%EC within stromal cells and MRD status at day +78) allowed classification of BCP-ALL into three risk groups with median DFS of: 3.9, 3.1 and 1.1 years, respectively (p = 0.001). These results were confirmed in two validation cohorts of childhood BCP-ALL (n = 74) (p = 0.001) and adult BCP-ALL (n = 40) (p = 0.004) treated at different centers. In summary, our findings suggest that an imbalanced EC/MSC ratio in BM at day +78 of therapy is associated with a shorter DFS of BCP-ALL patients, independently of their MRD status. Further prospective studies are needed to better understand the pathogenic mechanisms involved.

Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15-20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40-85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.