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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.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.

Glutathione peroxidases (GPxs) are a family of enzymes comprising eight members known for their peroxidase activity, which helps relieve oxidative stress by reducing hydrogen peroxide and lipid peroxides. GPxs play a crucial role in tumorigenesis, affecting DNA integrity, proliferation, cell adhesion, and survival. However, a comprehensive analysis of the expression and prognostic relevance of GPx members in gastric cancer (GC) remains underexplored. This study explored the relationship between GPx mRNA expression and prognosis in GC patients across different Lauren classifications (intestinal, diffuse, and mixed types). We found that GPx1 and GPx4 were highly expressed in all GC subtypes compared to normal tissues, while GPx7 expression was notably elevated in mixed-type GC. These findings were consistent across multiple Oncomine datasets and partially validated in TCGA GC versus normal samples. Kaplan-Meier survival analysis showed that high mRNA expression of GPx3, GPx5, GPx6, and GPx7 was associated with poor overall survival (OS) at both 5- and 10-year intervals. In contrast, elevated GPx1 expression correlated with better OS at both 5 and 10 years. Additionally, high GPx4, GPx5, and GPx6/7 expression were linked to reduced first progression (FP), while increased GPx3, GPx4, and GPx6/7 levels were associated with shorter post-progression survival (PPS). These trends were consistent for both 5- and 10-year FP and PPS. Prognostic associations were partially validated using TCGA data. Subgroup analyses based on Lauren classification, clinicopathological features, and treatment further supported these observations. This study highlights the distinct prognostic roles of GPx family members in GC. High GPx1 expression is associated with favorable outcomes, whereas elevated levels of GPx3, GPx4, GPx5, and GPx6/7 are linked to poor prognosis in GC patients, including OS, FP, and PPS. In addition to confirming previous findings, this study suggests that GPx4, GPx5, and GPx6/7 could serve as valuable prognostic markers and potential therapeutic targets in GC. Further clinical studies are needed to validate these findings and explore GPx-targeted therapies for GC.

Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis and limited response to immunotherapy. Immune escape-related genes (IERGs) are increasingly recognized as critical regulators of tumor progression and immune evasion. However, their prognostic value in GBM remains unclear. This study aims to evaluate the clinical relevance of IERGs and develop a predictive gene signature to guide prognosis and characterize the tumor immune microenvironment (TIME). We performed a comprehensive analysis of IERGs using the TCGA GBM dataset. Prognostic IERGs were identified through univariate Cox regression, and a multivariate Cox model was used to develop a prognostic signature. Risk scores (IEScore) were calculated to classify patients into high- and low-risk groups. The signature was validated in two independent GBM cohorts. Its prognostic independence was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis confirmed the signature's reliability. TIME analysis was carried out using multiple deconvolution algorithms. Additionally, functional assays including CCK8, cell cycle, and apoptosis assays were conducted on PPP1R8-silenced U251 cells using CRISPR/Cas9 technology. Thirty-six IERGs were associated with GBM outcomes, with 20 linked to poor survival and 16 to better outcomes. Key genes, including STAT2, IFNGR2, and PPP1R8, formed a robust prognostic signature. High-risk patients had significantly poorer overall survival (OS) compared to low-risk patients. The signature showed strong predictive power with AUC values of 0.68, 0.73, and 0.76 for 2-, 3-, and 5-year survival, respectively. Validation in two independent cohorts confirmed its robustness. Immune cell infiltration analysis revealed distinct patterns in high- and low-risk groups, with the high-risk group showing a more aggressive and immunosuppressive tumor microenvironment. The signature also effectively stratified low-grade glioma patients across four independent datasets. Knockout of PPP1R8 in GBM cells using CRISPR/Cas9 inhibited cell proliferation and increased apoptosis. The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. It can guide patient stratification and inform therapeutic decisions for GBM and potentially low-grade gliomas (LGG). Furthermore, we identify PPP1R8 as a key regulator of GBM cell proliferation and growth, providing insights into the immune microenvironment's role in GBM progression.

Traditional Chinese medicine (TCM) has garnered attention for its potential in cancer therapy. Yinchen Wuling San (YWLS), a classical herbal formula, has been traditionally used for liver-related conditions, but its bioactive components and molecular mechanisms relevant to hematologic malignancies such as acute myeloid leukemia (AML) remain unclear. This study aims to identify the active compounds and potential molecular targets of Yinchen Wuling San in the context of AML through network pharmacology analysis, and to experimentally validate the effects of selected candidate compounds in AML models. Active ingredients from six YWLS herbs were screened via the TCMSP database using oral bioavailability ≥30% and DL ≥0.18 thresholds. Targets were predicted using SwissTargetPrediction, and AML-related genes were obtained from DisGeNET and GeneCards. Key overlapping targets were analyzed via STRING PPI networks and GO/KEGG enrichment. Molecular docking was performed between three core compounds (genkwanin, isorhamnetin, quercetin) and hub proteins (e.g., SRC) using Sybyl-X. ADME profiles were predicted using SwissADME, and molecular dynamics simulations (GROMACS) assessed complex stability. These compounds were further evaluated (viability, apoptosis, cell cycle, RT-qPCR, flow cytometry) and using an AML xenograft mouse model. Of 621 YWLS targets, 113 overlapped with 1,247 AML-related genes. PPI analysis identified hub genes, including AKT1, SRC, and EGFR. Enrichment analysis highlighted PI3K-AKT, MAPK, and JAK-STAT pathways. Genkwanin, isorhamnetin, and quercetin were predicted to target SRC, with strong molecular docking affinities. ADME analysis suggested favorable pharmacokinetics, and molecular dynamics simulations confirmed structural stability. , these compounds exhibited dose-dependent cytotoxicity, induced apoptosis, modulated the cell cycle, and downregulated SRC expression. Notably, Genkwanin promoted CD8 T cell proliferation and inhibited leukemia growth, improving survival in a leukemia xenograft model. YWLS compounds, particularly Genkwanin, exhibit significant anti-leukemic activity via apoptosis induction, cell cycle modulation, and promote T cells proliferation. Genkwanin emerges as a promising therapeutic candidate for AML, warranting further clinical investigation.

Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited. We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature's independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology. Low-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature's validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis. This FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Acute myeloid leukemia (AML) is one of the most aggressive hematological malignancies with a low 5-year survival rate and high rate of relapse. Developing more efficient therapies is an urgent need for AML treatment. Accumulating evidence showed that ferroptosis, an iron-dependent form of programmed cell death, is closely correlated with cancer initiation and clinical outcome through reshaping the tumor microenvironment. However, understanding of AML heterogeneity based on extensive profiling of ferroptosis signatures remains to be investigated yet. Herein, five independent AML transcriptomic datasets (TCGA-AML, GSE37642, GSE12417, GSE10358, and GSE106291) were obtained from the GEO and TCGA databases. Then, we identified two ferroptosis-related molecular subtypes (C1 and C2) with distinct prognosis and tumor immune microenvironment (TIME) by consensus clustering. Patients in the C1 subtype were associated with favorable clinical outcomes and increased cytotoxic immune cell infiltration, including CD8 + /central memory T cells, natural killer (NK) cells, and non-regulatory CD4 + T cells while showing decreased suppressive immune subsets such as M2 macrophages, neutrophils, and monocytes. Functional enrichment analysis of differentially expressed genes (DEGs) implied that cell activation involved in immune response, leukocyte cell–cell adhesion and migration, and cytokine production were the main biological processes. Phagosome, antigen processing and presentation, cytokine–cytokine receptor interaction, B-cell receptor, and chemokine were identified as the major pathways. To seize the distinct landscape in C1 vs. C2 subtypes, a 5-gene prognostic signature (LSP1, IL1R2, MPO, CRIP1, and SLC24A3) was developed using LASSO Cox stepwise regression analysis and further validated in independent AML cohorts. Patients were divided into high- and low-risk groups, and decreased survival rates were observed in high- vs. low-risk groups. The TIME between high- and low-risk groups has a similar scenery in C1 vs. C2 subtypes. Single-cell-level analysis verified that LSP1 and CRIP1 were upregulated in AML and exhausted CD8 + T cells. Dual targeting of these two markers might present a promising immunotherapeutic for AML. In addition, potential effective chemical drugs for AML were predicted. Thus, we concluded that molecular subtyping using ferroptosis signatures could characterize the TIME and provide implications for monitoring clinical outcomes and predicting novel therapies.

BACKGROUNDChronic graft-versus-host disease (cGVHD) is a serious complication of allogeneic hematopoietic cell transplantation (HCT). More accurate information regarding the risk of developing cGVHD is required. Bone marrow (BM) grafts contribute to lower cGVHD, which creates a dispute over whether risk biomarker scores should be used for peripheral blood (PB) and BM.METHODSDay 90 plasma proteomics from PB and BM recipients developing cGVHD revealed 5 risk markers that were added to 8 previous cGVHD markers to screen 982 HCT samples of 2 multicenter Blood and Marrow Transplant Clinical Trials Network (BMTCTN) cohorts. Each marker was tested for its association with cause-specific hazard ratios (HRs) of cGVHD using Cox-proportional-hazards models. We paired these clinical studies with biomarker measurements in a mouse model of cGVHD.RESULTSSpearman correlations between DKK3 and MMP3 were significant in both cohorts. In BMTCTN 0201 multivariate analyses, PB recipients with 1-log increase in CXCL9 and DKK3 were 1.3 times (95% CI: 1.1-1.4, P = 0.001) and 1.9 times (95%CI: 1.1-3.2, P = 0.019) and BM recipients with 1-log increase in CXCL10 and MMP3 were 1.3 times (95%CI: 1.0-1.6, P = 0.018 and P = 0.023) more likely to develop cGVHD. In BMTCTN 1202, PB patients with high CXCL9 and MMP3 were 1.1 times (95%CI: 1.0-1.2, P = 0.037) and 1.2 times (95%CI: 1.0-1.3, P = 0.009) more likely to develop cGVHD. PB patients with high biomarkers had increased likelihood to develop cGVHD in both cohorts (22%-32% versus 8%-12%, P = 0.002 and P < 0.001, respectively). Mice showed elevated circulating biomarkers before the signs of cGVHD.CONCLUSIONBiomarker levels at 3 months after HCT identify patients at risk for cGVHD occurrence.FUNDINGNIH grants R01CA168814, R21HL139934, P01CA158505, T32AI007313, and R01CA264921.

Leukemia stem cells (LSCs) are a small yet powerful subset of leukemic cells that possess the ability to self-renew and have a long-term tumorigenic capacity, playing a crucial role in both leukemia development and therapy resistance. These LSCs are influenced by external and internal factors within the bone marrow niche. By delving into the intricate interplay between LSCs and their immune environment, we can pave the way for innovative immunotherapies that target both the malignant stem cells and the suppressive immune microenvironment, addressing both the “seed” and the “soil” simultaneously. Through the analysis of public datasets and patient samples, we show that elevated IL1RL1 expression correlates with poor prognosis and therapy resistance in acute myeloid leukemia (AML). At the core of this process, stem cell leukemogenesis initiation and maintenance signals are driven by a stress-induced IL-33/IL1RL1 autocrine loop. This LSC-induced IL-33/IL1RL1 signaling fosters an immune regulatory microenvironment. Therefore, IL1RL1 emerges as a promising therapeutic target, with IL1RL1-specific T cell-engaging bispecific antibodies holding great potential as cutting-edge immunotherapeutics for AML. High IL1RL1 correlates with poor survival in acute myeloid leukemia. A stress-driven IL-33/IL1RL1 loop induces leukemogenesis and a tolerogenic immune environment. Targeting this axis with bispecific antibodies offers a promising treatment.

Understanding the role of the STAT family in gastric cancer (GC) is essential for developing targeted therapies and improving patient outcomes. However, comprehensive analysis of STAT expression and its prognostic significance in GC is limited. This study aims to address this gap by examining STAT expression in normal and GC tissues and evaluating its prognostic value across clinical subgroups. STAT mRNA expression levels were compared between tumor and normal tissues using fold change analysis. Kaplan-Meier curves assessed the correlation between STAT expression and clinical outcomes, with statistical significance determined by the Log-rank test and hazard ratios (HR) with 95% confidence intervals. Subset analyses evaluated STAT expression across GC subtypes and its prognostic value, including in patients with oncogenic mutations. Most STAT family members, except STAT4, showed increased expression in GC tissues compared to normal tissues, consistent across various clinical subgroups, suggesting a role in GC pathogenesis. Kaplan-Meier analysis revealed the prognostic significance of STATs in GC. High STAT1 expression was associated with improved overall survival (OS), first progression (FP), and post-progression survival (PPS), indicating a favorable prognosis. In contrast, elevated STAT5A, STAT5B, and STAT6 expression correlated with poor prognosis. Subgroup analysis highlighted the consistent prognostic value of STATs across different histological subtypes, particularly in intestinal-type GC. Additionally, STAT expression had differential prognostic implications based on HER2 status. HER2-positive GC patients with high STAT expression had worse OS and FP rates, while HER2-negative patients with high STAT1 expression had better survival outcomes. This study provides valuable insights into STAT expression patterns and their prognostic significance in GC. The upregulation of STATs, except STAT4, suggests their involvement in GC oncogenesis. Notably, high STAT1 expression is a favorable prognostic marker, while increased STAT5A, STAT5B, and STAT6 expression correlates with poor prognosis. These findings underscore the potential of STATs as prognostic markers in GC, guiding personalized treatment strategies and improving patient outcomes.