The Role of MicroRNA in Graft-Versus-Host-Disease: A Review

Pitea, Martina; Canale, Filippo Antonio; Porto, Gaetana; Verduci, Chiara; Utano, Giovanna; Policastro, Giorgia; Alati, Caterina; Santoro, Ludovica; Imbalzano, Lucrezia; Martino, Massimo

doi:10.3390/genes14091796

Cited by 4 publications

(3 citation statements)

References 59 publications

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“…Examples of such targeted therapies includes inhibition of the Janus kinase (JAK) [25][26][27], Bruton's tyrosine kinase (BTK) [28][29][30], and Rho-associated coiled-coil-containing protein kinase 2 (ROCK2) [31] signaling pathways, each of which now have FDA-approved medications for management of steroid-refractory acute and/or chronic GvHD [32]. Our findings are in agreement with other reports such as the association of microRNA with acute and chronic GvHD [33].…”

Section: Discussionsupporting

confidence: 90%

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Rowley,

Gunning,

Pelliccia

et al. 2024

Cancers

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Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT). We performed RNA analysis of 1408 candidate genes in bone marrow samples obtained from 167 patients undergoing HSCT. RNA expression data were used in a machine learning algorithm to predict the presence or absence of aGvHD using either random forest or extreme gradient boosting algorithms. Patients were randomly divided into training (2/3 of patients) and testing (1/3 of patients) sets. Using post-HSCT RNA data, the machine learning algorithm selected 92 genes for predicting aGvHD that appear to play a role in PI3/AKT, MAPK, and FOXO signaling, as well as microRNA. The algorithm selected 20 genes for predicting survival included genes involved in MAPK and chemokine signaling. Using pre-HSCT RNA data, the machine learning algorithm selected 400 genes and 700 genes predicting aGvHD and overall survival, but candidate signaling pathways could not be specified in this analysis. These data show that NGS analyses of RNA expression using machine learning algorithms may be useful biomarkers of aGvHD and overall survival for patients undergoing HSCT, allowing for the identification of major signaling pathways associated with HSCT outcomes and helping to dissect the complex steps involved in the development of aGvHD. The analysis of pre-HSCT bone marrow samples may lead to pre-HSCT interventions including choice of remission induction regimens and modifications in patient health before HSCT.

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Section: Discussionsupporting

confidence: 90%

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Rowley,

Gunning,

Pelliccia

et al. 2024

Cancers

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“…For prompt diagnosis, a precise prognosis, and efficient therapy of aGVHD, it is crucial to find trustworthy, non-invasive biomarkers that may be used to predict, and evaluate the outcomes in aGVHD following allo-HSCT [1,11,19,20]. Circulating miRNAs in plasma, due to their stability and accessibility, have attracted considerable attention as potential noninvasive diagnostic, prognostic, and predictive biomarkers in aGVHD after allo-HSCT [11,21,22].…”

Section: Discussionmentioning

confidence: 99%

Diagnosis of Cutaneous Acute Graft‑Versus‑Host Disease Through Circulating Plasma miR‐638, miR‐6511b‐5p, miR‐3613‐5p, miR‐455‐3p, miR‐5787, and miR‐548a‐3p as Prospective Noninvasive Biomarkers Following Allogeneic Hematopoietic Stem Cell Transplantation

Izadifard,

Ahmadvand,

Pashaiefar

et al. 2024

Clinical Transplantation

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BackgroundThere are currently no laboratory tests that can accurately predict the likelihood of developing acute graft‐versus‐host disease (aGVHD), a patient's response to treatment, or their survival chance. This research aimed to establish circulating miRNAs as diagnostic, prognostic, or predictive biomarkers of aGVHD.MethodsIn a prospective cohort, we studied the incidence of cutaneous aGVHD in AML patients undergoing allo‐HSCT at Shariati Hospital in Tehran, Iran during 2020–2023. Patients with cutaneous aGVHD were labeled as the case group, while patients without cutaneous aGVHD were selected as the control group. Accordingly, the expression levels of six significant miRNAs (miR‐638, miR‐6511b‐5p, miR‐3613‐5p, miR‐455‐3p, miR‐5787, miR‐548a‐3p) were evaluated by quantitative reverse transcription–polymerase chain reaction (RTqPCR) in three different time‐points: before transplantation, on day 14 and day 21 after transplantation.ResultsThe levels of plasma miR‐455‐3p, miR‐5787, miR‐638, and miR‐3613‐5p were significantly downregulated, while miR‐548a‐3p, and miR‐6511b‐5p were significantly upregulated in individuals with cutaneous aGVHD in comparison to patients without GVHD. Additionally, the possibility for great diagnostic accuracy for cutaneous aGVHD was revealed by ROC curve analysis of differentially expressed miRNAs (DEMs).ConclusionThe study findings encourage us to hypothesize that the aforementioned miRNAs may contribute to the predominance of aGVHD, particularly low‐grade cutaneous aGVHD.

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“…According to a murine model of acute GVHD, the infusion of miR-223 agomiR resulted in symptom relief and decreased production of inflammatory cytokines [210]. Chronic GVHD has been associated with the dysregulated expression of miR-122-5p, miR-148-3p, miR-192-5p, miR-365-3p and miR-378-3p [211,212].…”

Section: Applications Of Mirnas In Transplantation Immunologymentioning

confidence: 99%

Role of microRNAs in Immune Regulation with Translational and Clinical Applications

Gaál

2024

IJMS

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MicroRNAs (miRNAs) are 19–23 nucleotide long, evolutionarily conserved noncoding RNA molecules that regulate gene expression at the post-transcriptional level. In this review, involvement of miRNAs is summarized in the differentiation and function of immune cells, in anti-infective immune responses, immunodeficiencies and autoimmune diseases. Roles of miRNAs in anticancer immunity and in the transplantation of solid organs and hematopoietic stem cells are also discussed. Major focus is put on the translational clinical applications of miRNAs, including the establishment of noninvasive biomarkers for differential diagnosis and prediction of prognosis. Patient selection and response prediction to biological therapy is one of the most promising fields of application. Replacement or inhibition of miRNAs has enormous therapeutic potential, with constantly expanding possibilities. Although important challenges still await solutions, evaluation of miRNA fingerprints may contribute to an increasingly personalized management of immune dysregulation with a remarkable reduction in toxicity and treatment side effects. More detailed knowledge of the molecular effects of physical exercise and nutrition on the immune system may facilitate self-tailored lifestyle recommendations and advances in prevention.

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The Role of MicroRNA in Graft-Versus-Host-Disease: A Review

Cited by 4 publications

References 59 publications

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Diagnosis of Cutaneous Acute Graft‑Versus‑Host Disease Through Circulating Plasma miR‐638, miR‐6511b‐5p, miR‐3613‐5p, miR‐455‐3p, miR‐5787, and miR‐548a‐3p as Prospective Noninvasive Biomarkers Following Allogeneic Hematopoietic Stem Cell Transplantation

Role of microRNAs in Immune Regulation with Translational and Clinical Applications

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