Harnessing TDO2-mediated Metabolism to Modulate Immune Rejection in Liver Transplantation
Notice bibliographique
Résumé
Acute cellular rejection (ACR) in liver transplantation (LT) is a complex process involving immune and nonimmune cells, with graft survival being influenced by alloimmune pathways, metabolic reprogramming, and cellular interactions within the liver environment. In most of the published studies, ACR has been evaluated with a focus on immune cells. However, recent evidence suggests that nonimmune liver cells, including hepatocytes, endothelial cells, and cholangiocytes, also play a role in modulating immune responses through various signaling.1,2 Despite significant progress, their precise role in immunomodulation remains unclear. The findings that tryptophan (Trp) metabolism through the kynurenine (Kyn) pathway can influence graft rejection or tolerance has led to the development of potential therapeutic targets, including indoleamine 2,3-dioxygenase 1 (IDO1), a Trp-metabolizing enzyme. However, despite extensive studies so far, its role in LT and rejection remains controversial.3,4 The study by Li et al5 provided important new insights into tryptophan 2,3-dioxygenase (TDO2), the primary enzyme for Trp metabolism in hepatocytes, and its role in liver graft rejection. Using a TDO2 knockout (TDO2-KO) rat model, they showed that TDO2 deficiency worsens ACR, with increased liver injury and inflammation and a negative impact on graft survival. These findings suggest that TDO2 plays a critical role in maintaining immune homeostasis. A major strength of the study is the use of an integrative approach with TDO2-KO models, transcriptomic analysis, and immune profiling to assess the impact of TDO2 deficiency on liver graft immunity. Their findings reveal that TDO2 deficiency promotes a proinflammatory environment with increased levels of tumor necrosis factor alpha and interferon-gamma, reduced interleukin-10, and increased macrophage polarization toward the M1 phenotype, all indicators of allograft rejection. Furthermore, the study shows that TDO2 deficiency negatively affects immune homeostasis within the graft, leading to increased CD8+ T-cell activation and a decrease in CD4+ regulatory T cells, a pattern that correlates with severe ACR and decreased graft survival. Additionally, TDO2 deficiency disrupts the PD-1 (programmed cell death protein 1)/PD-L1 (programmed cell death ligand 1) pathway, a key immune checkpoint involved in transplant tolerance and cancer immunotherapy, suggesting that TDO2 also plays a role in regulating immune signaling within the graft environment. Findings by Li et al contributed to a growing body of evidence on the Kyn pathway as a key regulator of immune function in transplantation and cancer immunology. Previous studies have shown that IDO1-mediated Kyn production suppresses T-cell activation and promotes immune tolerance in various models.6,7 However, the role of IDO1 in LT has been inconsistent, with some studies supporting its tolerogenic effects and others reporting no significant impact on rejection or survival.8,9 Furthermore, the failure of phase III trials combining IDO1 and PD-1 inhibitors in melanoma raises concerns about whether IDO1 alone can provide sustained immune control.10 In contrast to IDO1, TDO2 is constitutively expressed in hepatocytes, suggesting a more stable role in rejection. The study by Li et al5 supported this, showing that TDO2 deficiency worsens rejection and interrupts immune balance. Their findings not only align with studies highlighting the role of TDO2 in liver immune homeostasis5,6 but also raise new questions that need further investigation. A key debate lies in the contrasting roles of TDO2 in transplantation versus cancer. Li et al5 showed that TDO2 supports immune tolerance in LTs, but cancer studies suggest that it helps tumors evade the immune system by suppressing antitumor immunity.8 This raises important questions about whether the role of TDO2 depends on the immune context, favoring tolerance in transplantation but immune evasion in cancer. Future research should examine how TDO2 functions in different immune environments and explore targeted strategies to maximize its benefits while minimizing potential risks. Another unresolved point is whether IDO1 and TDO2 work independently or compensate for each other. Both enzymes break down Trp and produce Kyn, and it is unclear whether IDO1 compensates for TDO2 loss in certain cases. Investigating double-knockout models (IDO1/TDO2-KO) could clarify their individual roles in transplant tolerance. Despite the strengths of the study by Li et al, several limitations should be acknowledged. First, the study uses a single knockout model (TDO2-KO rats), which may not fully account for potential compensatory mechanisms activated in response to TDO2 deficiency. Future studies using conditional knockout models or pharmacological inhibitors would help validate these findings. Although cytokine profiling and metabolic studies were performed, direct functional assays on immune cells (eg, T-cell activation assays, macrophage polarization studies in vivo) would provide deeper mechanistic insights. Second, although Li et al provided valuable insights into acute rejection, they do not explore long-term graft survival or chronic mechanisms of graft injury. Because metabolic immune regulation likely impacts both acute and chronic transplant outcomes, future studies should assess the role of TDO2 in fibrosis, regulatory immune networks, and chronic rejection. Finally, it remains unclear whether inhibiting or enhancing TDO2 would be beneficial in different clinical contexts. Understanding how to selectively manipulate TDO2 in LT without compromising systemic immune function is essential for clinical applications. Further research should validate these findings in human LT recipients by analyzing TDO2 expression, Trp-Kyn metabolism, and immune responses in clinical samples. Additionally, exploring TDO2 inhibitors, Kyn analogs, or aryl hydrocarbon receptor modulators in preclinical models may help develop new therapeutic strategies to improve transplant tolerance and long-term graft survival.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».