Acute myeloid leukemia (AML) is a malignant blood disease with a poor prognosis. Over the past decades, intensive chemotherapy and hematopoietic stem cell transplant (HSCT) have been the main treatments, with allo-HSCT being considered the only curative method. With a deeper understanding of leukemia mechanisms and the development of structural pharmacology, many small molecule targeted therapies have been developed. Among them, BCL-2 inhibitors, IDH1 inhibitors, and FLT3 inhibitors are the most popular in clinical practice, dramatically changing the prognosis of refractory AML. However, many AML patients still have a poor prognosis due to the lack of available targets or primary/acquired resistance to targeted therapy.

With recent technological advances, protein quantitative trait loci (pQTL) and expression quantitative trait loci (eQTL) datasets have become crucial for studying human biology and pathophysiology. These datasets help bridge the gap between the genome and diseases. Mendelian randomization (MR) analysis has been widely used for drug target development and drug repurposing in recent years. As a genetic instrumental variable analysis, MR usually uses single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) as genetic instruments to estimate the causal effect of an exposure on an outcome. Our objective is to elucidate the pathogenesis of leukemia through this methodology, identify novel clinically significant therapeutic targets, and ultimately render AML a curable disease without requiring allogeneic hematopoietic stem cell transplantation in theory.

In this study, a total of 88 plasma proteins in the pQTL data have been found to be associated with AML using MR. Among these, TCL1A (OR: 1.66; 95% CI: 1.46-1.88 per 1-SD higher concentration)was the most strongly associated with AML. The IVW analysis revealed a positive correlation between TCL1A-eQTL and AML (P = 1.699 × 10−6, OR = 2.080, 95% CI: 1.541–2.808). Furthermore, rs78986913 was identified as a shared variant for both TCL1A and AML through B0ayesian colocalization analysis, suggesting this locus may be a key mechanism through which TCL1A influences AML pathogenesis. ROC analysis showed TCL1A had an AUC of 0.985 (95% CI: 0.973–0.996), indicating excellent diagnostic potential. High TCL1A expression was associated with low overall survival rates in AML patients (P < 0.001), especially in the FAB M0 and M2 subgroups. Furthermore, TCL1A exhibits high tissue specificity, almost exclusively expressed in lymph nodes, tonsils, spleen, appendix, bone marrow, and other related tissues. Cell lines enriched with TCL1A RNA primarily included leukemia and lymphoma cells. Additionally, our study revealed that all of the human leukemia cell lines MOLM-13 (2.02 ± 0.28), MV4-11 (23.73 ± 1.45), THP-1 (35.98 ± 5.16), KG-1a (12.77 ± 4.88), SKM-1 (12.48 ± 1.18), HL-60 (2.65 ± 0.46), NB4 (2.25 ± 0.46), SKNO-1 (239.38 ± 30.83), NOMO-1 (41.13 ± 11.30), and MONO-MAC-1 (22.32 ± 3.94) showed higher TCL1A levels compared with the human bone marrow stromal cell line HS-5 (1.03 ± 0.25). Notably, most of the human leukemia cell lines (including MV4-11, THP-1, KG-1a, SKM-1, SKNO-1, NOMO-1, and MONO-MAC-1) showed higher TCL1A levels compared with solid tumor cell lines HT29 (0.18 ± 0.05), SW480 (1.08 ± 0.31), HCT116 (2.82 ± 0.53), MDA-MB-231 (2.70 ± 0.41), and A-549 (0.65 ± 0.11) .

High-throughput virtual screening (HTVS) was conducted to identify potential TCL1A inhibitors. The X-ray crystal structure of human TCL1A, retrieved from the PDB database (PDB ID: 1JSG), was refined using the Protein Preparation Wizard module. A total of 1,620,219 small molecules were generated through conformational sampling, resulting in 2,585,846 distinct conformations. Following HTVS, we identified 10 small molecules, finding that Bletilloside A (id number: 2292159-89-6) is one of the most fitting small molecules for the TCL1A protein pocket.

In summary, we successfully identified a novel potential drug target TCL1A for AML through MR analysis, in accordance with bioinformatics technology and experimental validation. And potential therapeutic drugs were screened through HTVS. There is a causal relationship between TCL1A and AML. The expression level of TCL1A deserves further monitoring in clinical settings, and the benefits of targeting TCL1A should be further validated.

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2025
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