Leptin-Enhanced JAK-STAT Signaling in Acute Myeloid Leukemia-Derived Mesenchymal Stromal Cells and Its Implications for Disease Progression
Bibliographic record
Abstract
Introduction Acute Myeloid Leukemia (AML) involves the rapid growth of abnormal myeloid cells in the bone marrow. This growth disrupts normal blood production. In the marrow, mesenchymal stromal cells (MSCs) are a key factor and are known to influence AML progression and treatment resistance. However, their genetic and molecular characteristics remain underexplored. AML-MSCs reportedly exhibit pro-inflammatory activity, with genes such as IL6 and TLR4 being implicated. The Leptin-mediated JAK-STAT pathway is a crucial player, involved in cell proliferation and immune evasion. Leptin, known for its role in metabolism, also influences immune response, making it a focus for understanding leukemia. This study aimed to identify altered genes and pathways in AML-MSCs to understand their roles in leukemia and aid in developing new treatment targets for improving patient outcomes. Methods MSCs were isolated using plastic adherence from bone marrow aspirates of 3 AML patients and 3 normal controls. Samples were matched for age and sex. Bulk RNA sequencing was conducted at passage 3. Reads were mapped with STAR, and counts were generated by HTseq. Differential expression analysis was performed with DESeq2; significant genes were identified with an adjusted p-value < 0.05 and a log2 fold change > 1.5. Pathway analysis was conducted using ShinyGO and the KEGG database; pathways were deemed significant if they had a false discovery rate (FDR) < 0.05. Furthermore, the study was extended to include RNA analysis for 24 AML-MSC cases paired with their leukemic fractions (LCs). Results RNA-seq analysis identified 666 differentially expressed genes in AML-MSCs. Following filtering, 177 genes were upregulated, and 248 genes were downregulated. Pathway enrichment analysis revealed significant upregulation in several pathways, including Toll-like receptor (TLR), Tumor necrosis factor (TNF), and JAK-STAT signaling pathways. The TLR pathway was associated with upregulated TLR2 (log2FC = -2.5250, p-adj = 0.0469). This suggests an enhanced inflammatory environment in the bone marrow. The TNF pathway showed upregulation of IL6 (log2FC = -2.9998, p-adj = 0.0089). This further contributes to a chronic inflammatory state. Of note, the JAK-STAT pathway was markedly enriched, with upregulated LEP (log2FC = -5.3273, p-adj = 0.0167), which encodes leptin, and STAT1 (log2FC = -2.2720, p-adj = 0.0007). In brief, pro-inflammatory pathways were prevalent in the analysis. The JAK-STAT pathway was particularly prominent due to its overlap with other upregulated pathways in this study and its known role in MSC-LC interactions. To validate these findings, the study was expanded to include 24 AML-MSC cases, with paired LCs. Analysis of specific genes from the preliminary data confirmed several JAK-STAT pathway components in the larger dataset. LEP showed the highest log2 fold change (9.2427, p-adj: 2.5445 x 10-34). Finally, downregulated pathways were also explored to gain a comprehensive understanding of AML-MSC molecular alterations. Key pathways included the cell cycle and necroptosis. The cell cycle pathway revealed that the gene MCM5 had a log2 fold change of 1.6953 (p-adj = 0.0003). This suggests impaired cell cycle progression and reduced MSC proliferation. The necroptosis pathway demonstrated significant downregulation of H2AC14 (log2FC = -3.1342, p-adj = 0.0068). Consequently, this suggests reduced programmed cell death, which could allow senescent MSCs to survive longer and support AML cells. Conclusion Leptin may play a vital role in the leukemic microenvironment. Elevated leptin levels can activate the JAK-STAT pathway in MSCs through autocrine binding to LEPR. This activation may increase pro-inflammatory cytokines like IL6 and TNF-α, creating an environment that supports AML cell survival and proliferation while impairing normal blood cell production. Additionally, disturbances in cell cycle processes further complicate the microenvironment. Therefore, targeting leptin signaling or its JAK-STAT pathway effectors could disrupt this pro-leukemic environment. Overall, this work demonstrates the significant involvement of MSCs in the microenvironment of AML and identifies notable genes and pathways in AML-MSCs that may be prospective targets for therapeutic interventions. These discoveries open up new paths for leukemia research and treatment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".