Allogeneic hematopoietic cell transplantation (allo-HCT) is an essential therapeutic modality for patients with hematological malignancies and other blood disorders. Unfortunately, acute graft-versus-host disease (aGVHD) remains a major source of morbidity and mortality following allo-HCT, which limits its use in a broader spectrum of patients. Chronic graft-versus-host disease (cGVHD) also remains the most common long-term complication of allo-HCT, occurring in reportedly 30-70% of patients surviving more than 100 days. Chronic GVHD is also the leading cause of non-relapse mortality (NRM) occurring more than 2 years after HCT for malignant disease. Graft versus tumor (GVT) is a major component of the overall beneficial effects of allogeneic HCT in the treatment of hematological malignancies. Better understanding of GVHD pathogenesis is important to identify new therapeutic targets for GVHD prevention and therapy. Emerging data suggest opposing roles for different T cell subsets, e.g., IFN-γ producing CD4+ and CD8+ T cells (Th1 and Tc1), IL-4 producing T cells (Th2 and Tc2), IL-17 producing T cells (Th17 and Tc17), IL-9 producing T cells (Th9 and Tc9), IL-22 producing T cells (Th22), T follicular helper cells (Tfh), regulatory T-cells (Treg) and tissue resident memory T cells (Trm) in GVHD and GVT etiology. In this review, we first summarize the general description of the cytokine signals that promote the differentiation of T cell subsets and the roles of these T cell subsets in the pathogenesis of GVHD. Next, we extensively explore preclinical findings of T cell subsets in both GVHD/GVT animal models and humans. Finally, we address recent findings about the roles of T-cell subsets in clinical GVHD and current strategies to modulate T-cell differentiation for treating and preventing GVHD in patients. Further exploring and outlining the immune biology of T-cell differentiation in GVHD that will provide more therapeutic options for maintaining success of allo-HCT.

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MicroRNAs (miRNAs) regulate the functions of granulosa cells by interacting with their target mRNAs. Insulin receptor substrate 2 (IRS2) is one of the targets of miR-431 and can be regulated by ovarian hormones. However, the role of miR-431 and the associated signal transduction pathway in ovarian development has not been studied previously. In this study, we first analyzed the expression of miR-431 and IRS2 following stimulation with pregnant mare serum gonadotropin (PMSG) during the estrous cycle or different stages of ovarian development in mice. Subs equently, we investigated the role, function, and signaling pathway of miR-431 in the human granulosa cell line, COV434. The results showed that follicle stimulating hormone (FSH) gradually decreased miR-431 levels, induced IRS2, and promoted pAKT expression. Moreover, miR-431 overexpression and IRS2 knockdown attenuated AKT activation, inhibited cell proliferation, and decreased estradiol (E 2) and progesterone (P 4) synthesis. Further, luciferase reporter assay demonstrated that IRS2 was a direct target of miR-431. In conclusion, this study demonstrated that miR-431 regulates granulosa cell function through the IRS2/PI3K/AKT signaling pathway.

Aberrant RNA alternative splicing (AS) variants play critical roles in tumorigenesis and prognosis in human cancers, here we conducted a comprehensive profiling of aberrant AS events in AML. RNA AS profile, including 7 AS types, and the Percent Spliced In (PSI) value for each patient was generated by SpliceSeq using RNA-seq data from TCGA. Univariate followed by multivariate Cox regression analysis were used to identify survival-related AS events and develop the AS signatures.  A nomogram was developed, and its predictive efficacy was assessed. 27,892 AS events, and 3,178 events were associated with overall survival (OS) after strict filtering. Parent genes of survival-associated AS events were mainly enriched in leukemia-associated processes including chromatin modification, autophagy, and T cell receptor signaling pathway. The 10 AS signatures based on 7 types of AS events showed better efficacy in predicting OS of patients than those built on a single AS event type. The area under curve (AUC) value of the 10 AS signature for 3-year OS was 0.91. Gene set enrichment analysis (GSEA) confirmed that these survival-related AS events contribute to AML progression. Moreover, the nomogram showed good predictive performance for patients’ prognosis. Finally, the correlation network of AS variants with splicing factor genes found potential important regulatory genes in AML. This study presented a systematic analysis of survival-related AS events and developed AS signatures for predicting the patient’s survival. Further studies are needed to validate the signature in independent AML cohorts and might provide a promising perspective for developing therapeutic targets.