Comprehensive characterization of TGFB1 across hematological malignancies.

TGFB1, which encodes TGF-ß1, a potent cytokine regulating varies cellular processes including immune responses. TGF-ß1 plays context-dependent roles in cancers and is increasingly recognized as a therapeutic target to enhance immunotherapy responses. We comprehensively evaluated expression of TGFB1 and its clinical and biological effects across hematological malignancies. TGFB1 expression was first explored using data from the GTEx, CCLE, and TCGA databases. The expression and clinical significances of TGFB1 in hematological malignancies were analyzed using Hemap and our In Silico curated datasets. We also analyzed the relationship between TGFB1 with immune scores and immune cell infiltrations in Hemap. We further assessed the value of TGFB1 in predicting immunotherapy response using TIDE and real-world immunotherapy datasets. TGFB1 showed a hematologic-tissue-specific expression pattern both across normal tissues and cancer types. TGFB1 expression were broadly dysregulated in blood cancers and generally associated with adverse prognosis. TGFB1 expression were associated with distinct TME properties among different blood cancer types. In addition, TGFB1 expression was found to be a useful marker in predicting immunotherapy responses. Our results suggest that TGFB1 is broadly dysregulated in hematological malignancies. TGFB1 might regulate the immune microenvironment in a cancer-type-specific manner, which could be applied in the development of new targeted drugs for immunotherapy.

A novel methionine metabolism-related signature predicts prognosis and immunotherapy response in lung adenocarcinoma.

Recent research revealed methionine metabolism as a key mediator of tumor initiation and immune evasion. However, the relationship between methionine metabolism and tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unknown. Here, we comprehensively analyzed the genomic alterations, expression patterns, and prognostic values of 68 methionine-related regulators (MRGs) in LUAD. We found that most MRGs were highly prognostic based on 30 datasets including 5024 LUAD patients. Three distinct MRG modification patterns were identified, which showed significant differences in clinical outcomes and TME characteristics: The C2 subtype was characterized by higher immune score, while the C3 subtype had more malignant cells and worse survival. We developed a MethScore to measure the level of methionine metabolism in LUAD. MethScore was positively correlated with T-cell dysfunction and tumor-associated macrophages (TAMs), indicating a dysfunctional TME phenotype in the high MethScore group. In addition, two immunotherapy cohorts confirmed that patients with a lower MethScore exhibited significant clinical benefits. Our study highlights the important role of methionine metabolism in modeling the TME. Evaluating methionine modification patterns will enhance our understanding of TME characteristics and can guide more effective immunotherapy strategies.

m6A regulator-based methylation modification patterns and characterization of tumor microenvironment in acute myeloid leukemia.

RNA N6-methyladenosine (m6A) is the most common and intensively studied RNA modification that critically regulates RNA metabolism, cell signaling, cell survival, and differentiation. However, the overall role of multiple m6A regulators in the tumor microenvironment (TME) has not yet been fully elucidated in acute myeloid leukemia (AML). In our study, we explored the genetic and transcriptional alterations of 23 m6A regulators in AML patients. Three distinct molecular subtypes were identified and associated with prognosis, patient clinicopathological features, as well as TME characteristics. The TME characterization revealed that m6A patterns were highly connected with metabolic pathways such as biosynthesis of unsaturated fatty acids, cysteine and methionine metabolism, and citrate cycle TCA cycle. Then, based on the differentially expressed genes (DEGs) related to m6A molecular subtypes, our study categorized the entire cohort into three m6A gene clusters. Furthermore, we constructed the m6Ascore for quantification of the m6A modification pattern of individual AML patients. It was found that the tumor-infiltrating lymphocyte cells (TILs) closely correlated with the three m6A clusters, three m6A gene clusters, and m6Ascore. And many biological processes were involved, including glycogen degradation, drug metabolism by cytochrome P450, pyruvate metabolism, and so on. Our comprehensive analysis of m6A regulators in AML demonstrated their potential roles in the clinicopathological features, prognosis, tumor microenvironment, and particularly metabolic pathways. These findings may improve our understanding of m6A regulators in AML and offer new perspectives on the assessment of prognosis and the development of anticancer strategy.