Multiomics Characterization and Comprehensive Omics-Based Classification System in Adult Patients with B-Cell Acute Lymphoblastic Leukemia
Authors: Song Yang , Liu Ting , Hao Qishan , Fang Qiuyun , Gong Xiaoyuan , Li Yan , Wei Hui , Wang Min , Wang Jianxiang , Cheng Tao , Mi Yingchang 
Published: December 2024

ABSTRACT

BACKGROUND: Adult B-cell acute lymphoblastic leukemia (B-ALL) is a highly heterogeneous disease with a challenging prognosis. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the cornerstone of treatment for these population. Previous B-ALL classifications have mainly relied on transcriptomics for prognosis prediction. However, a more comprehensive classification system integrating diverse subtypes with definite prognosis and therapeutic implications in adult B-ALLs is currently lacking.

METHODS: We analyzed 391 adult B-ALL patients, including a real-world 88 cases (Ph positive 34, Ph negative 54), titled ‘ihCAMs-ALL’ (aged 34, 15-70), and two independent validation cohorts (GSE34861 N=194, Ph positive 78, Ph negative 116; GSE66005 N=109, Ph positive 42, Ph negative 67). Among ihCAMs-ALL, we conducted transcriptomic (RNA-seq), epigenetic methylation (Illumina 850K) and genomic mutation (Targeted NGS). In addition, 9 healthy donors and 9 patients with T-cell acute lymphoblastic leukemia (T-ALL) were enrolled for extensive omics-based comparisons. We classified patients based on multi-omics information by ten unsupervised algorithms and constructed the model called comprehensive omics-based classification system for B-cell ALL with therapeutic implications (COMBAT).

RESULTS: B-ALL patients exhibited unique epigenetic (hypomethylated state compared to T-ALL patients) and gene expression landscapes (immunocompromised state compared to healthy controls). Next, we compared methylation and transcriptomic of Ph negative B-ALLs and T-ALLs, key active regulons that were uniquely found associated with B-ALL, including BACH2, EBF1, ELK3, HIVEP1, JUNB, and ZNF296 (all Spearman's coefficients &gt; 0.8, all p &lt; 0.001). These data demonstrated that both the similarities and heterogeneity within the B-ALLs.

Next, we assessed the interplay between COMBAT clusters and clinical features. COMBAT stratified patients into three cohorts: (1) COMBAT1, characterized by high stem/myeloid antigen expression, low immune infiltration, endothelial cells enrichment, presented degraded hypomethylation in CIMP (CpG island methylator phenotype) ; (2) COMBAT2, defined as an inflamed subtype with immune exhaustion and activated inflammatory response pathways; and (3) COMBAT3, termed ‘proliferative subtype’, with MYC pathway activation and hypermethylation at enhancer regions in patients characterized by CIMP.

In Ph-negative B-ALLs, diagnostic FACS data revealed that COMBAT3 subgroup patients presented lower expression of myeloid-associated antigens CD13 (p=0.002) and CD33 (p=0.013), as well as stem cell-associated antigens CD34 (p=0.004) and HLA-DR (p=0.012) than COMBAT1-2. Meanwhile, COMBAT1-2 demonstrated lower complete remission (CR) rates compared to COMBAT3 (0% vs. 50% vs. 96.2%, p=0.0028). Ph-negative B-ALL patients undergoing allo-HSCT in the COMBAT3 group showed better overall survival (OS) than those in the COMBAT1-2 groups (estimated 3-year OS: 100% vs. 65.6%, log-rank test, p=0.034), suggesting a prognostic benefit of this subtype.

CONCLUSIONS: The COMBAT system redefines adult B-ALL subtypes, predicts immune characteristics, and delineates potential benefits from allo-HSCT for Ph-negative patients. These findings provide crucial insights into therapeutic options and outcomes for adult B-ALL patients, thereby enhancing our understanding of effective treatment strategies.