Toll-like Receptor-3 Ligation Induces Pro-Survival Signaling in Pediatric Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Abstract B cell precursor acute lymphoblastic leukemia (B-ALL) is the most common cancer in children, with a peak age of incidence of 2-5 years. In the majority of pediatric cases, B-ALL is initiated in utero, with full transformation from pre-leukemia to leukemia being driven by additional oncogenic events acquired in early childhood. Surprisingly, common in utero genetic events lead to the expansion of pre-leukemic clones in >1% of all newborns, yet only 1 in 100 of these infants go on to develop clinically overt leukemia in their lifetime. This suggests the presence of certain protective and/or non-protective mechanisms that influence the fate of pre-leukemic clones. While several epidemiological studies of early-life infection indicate a consequent increased risk for ALL, protective effects of infection exposure against ALL have also been reported. An infectious agent responsible for pro- or anti-leukemic effects has not been identified and a mechanistic explanation for the seemingly contradictory effects of early-life infection has not been defined. We have previously reported the ability of immune stimulation with infection-associated toll-like receptor (TLR) agonists to reduce pre-leukemic cell burden and delay leukemia onset in the Eμ-RET transgenic mouse model of hyperdiploid B-ALL. We observed that while TLR9 (CpG) and TLR7/8 (R848) ligands were effective at reducing viable pre-leukemic and leukemic cells, a TLR3 ligand (PolyI:C) appeared to have an opposite effect. In this study, we further investigate the potential pro-leukemic effect of TLR3 ligands (pathogenic dsRNA) on abnormal BCP cell behavior. Purified pre-leukemic or leukemic cells from Eu-ret mice were treated in vitro with TLR agonists and cell viability was assessed after 48 hours. In contrast to the reduced viability observed after exposure to TLR7/8 (R848) and TLR9 (CpG) ligands, a ~1.5-fold increase in viable cell recovery, compared to untreated cells, was observed after treatment with PolyI:C (p <0.05). Since PolyI:C binds other receptors in addition to TLR3, we then assessed PolyA:U, a synthetic dsRNA molecule signaling exclusively through TLR3. Treatment of purified pre-leukemic and leukemic cells with PolyA:U lead to an increase in viable cell recovery compared to untreated cells (p < 0.01), implicating TLR3 as the relevant receptor. This viable cell recovery correlated with reduced apoptosis and an increased proliferation index in PolyA:U treated samples. To assess the relevance of this TLR-induced activity for clinical B-ALL, we evaluated the responses of patient-derived B-ALL samples. A similar survival benefit was observed with primary B-ALL samples treated with TLR3, but not other TLR ligands. Consistent with observations from primary murine leukemia, CpG and R848 were able to induce in vitro killing of human leukemia cells, while PolyA:U promoted increased leukemia cell viability. As the overall outcome of early-life infection will also involve TLR-induce immune responses, we next assessed the effect of TLR3 agonists in the presence of immune effector cells. Bulk splenocytes from 1- to 12-week-old Eu-RET mice were cultured in the presence or absence of TLR agonists and viable cell recovery after 48 hours measured. In the presence of immune effector cells, the impact of pro-survival TLR3 signalling was diminished in an age-dependent manner, implicating neonatal immunity in the abnormal pro-leukemic response induced by TLR3 ligation. Overall, our results reveal previously unrecognized pro-survival signalling through TLR3 that could contribute to an early-life infection-driven progression of B-ALL. We are currently exploring the signaling pathway(s) responsible for this effect and evaluating the immune variables that influence pre-leukemia cell fate in vivo. This study will significantly enhance our mechanistic understanding of immune-mediated modification of B-ALL progression induced by early-life infection exposure. Disclosures No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".