Our study reveals that FDX1 can serve as a potential therapeutic target and prognostic marker for various malignancies due to its vital role in tumorigenesis and tumor immunity.Ferredoxin 1 (FDX1) functions by transferring electrons from NADPH to mitochondrial cytochrome P450 via the ferredoxin reductase and is the key regulator in copper-dependent cell death. Although mounting evidence supports a vital role for FDX1 in tumorigenesis of some cancers, no pan-cancer analysis of FDX1 has been reported. Therefore, we aimed to explore the prognostic value of FDX1 in pan-cancer and investigate its potential immune function. Based on data from The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, Human Protein Atlas, and Gene Set Cancer Analysis, we used a range of bioinformatics approaches to explore the potential carcinogenic role of FDX1, including analyzing the relationship between FDX1 expression and prognosis, DNA methylation, RNA methylation-related genes, mismatch repair (MMR) gene, microsatellite instability (MSI), tumor mutation burden (TMB), tumor microenvironment (TME), immune-related genes, and drug sensitivity in different tumors. The results show that FDX1 was lowly expressed in most cancers but higher in glioblastoma multiforme, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. Moreover, FDX1 expression was positively or negatively associated with prognosis in different cancers. FDX1 expression was significantly associated with DNA methylation in 6 cancers, while there was a correlation between FDX1 expression and RNA methylation-related genes and MMR gene in most cancers. Furthermore, FDX1 expression was significantly associated with MSI in 8 cancers and TMB in 10 cancers. In addition, FDX1 expression was also significantly correlated with immune cell infiltration, immune-related genes, TME, and drug resistance in various cancers. An experiment  Consequently, patients develop drug resistance to PD-1 due to toxic T-cell reactions  is characterized by a low redox potential, low molecular weight, and harbors at least one Fe-S cluster  (FDX1 on the long arm of chromosome 11 may be involved in the development of Lymphoproliferative disorders (LPD) (FDX1 (rs10488764) were associated with the risk of IgA nephropathy  directly targets FDX1 and inhibits FDX1-mediated Fe-S cluster biosynthesis, thereby promoting copper-dependent cell death in human breast cancer and lung adenocarcinoma cells  protein encoded by ferredoxin 1 ( cluster . FDX1 caile acid . FDX1 pl1 (SF-1) . FDX1 is1 (SF-1) . Furtherrs (LPD) . Anotherhropathy . Growing in mice . Moreovema cells . Severalma cells . Likewisesclomol . HoweverFDX1 expression levels systematically and to evaluate their relationship with prognosis in pan-cancer. We also assessed the relationship between FDX1 expression and DNA methylation, microsatellite instability (MSI), tumor mutation burden (TMB), and tumor microenvironment (TME) in pan-cancer. We used co-expression analysis to analyze the relationship between FDX1 expression and RNA methylation-related genes, mismatch repair (MMR) gene, immune-related genes, and drug sensitivity in these cancers. Moreover, we investigated the biological function of FDX1 in tumors using single-cell database and enrichment analysis and verified in vitro experiments with bladder cancer, clear cell renal cell carcinoma, and prostate cancer cell lines. Our results suggest that FDX1 may serve as a therapeutic target for various cancers and plays a vital role in tumor immunity by influencing MSI, TMB, and tumor-infiltrating immune cells.Therefore, we used the most up-to-date data from numerous databases, including The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Genotype Tissue-Expression (GTEx), Human Protein Atlas (HPA), and Gene Set Cancer Analysis (GSCA), to analyze https://xenabrowser.net/datapages/), as well as RNA expression data from 26 types of normal tissues of GTEx. Thirty-three types of cancer cell line expression matrix of RNA expression were downloaded from the CCLE database . Images of immunohistochemistry (IHC) and subcellular localization of FDX1 were downloaded from the HPA database (https://www.proteinatlas.org/).Gene expression, somatic mutations, and related clinical data from 33 types of cancer were downloaded from the UCSC Xena database , WT1 associated protein (WTAP), methyltransferase 3 N6-adenosine-methyltransferase complex catalytic subunit (METTL3), METTL14, RNA binding motif protein 15 (RBM15), RBM15B, zinc finger CCCH-type containing 13 (ZC3H13), alkB homolog 5, RNA demethylase (ALKBH5), FTO alpha-ketoglutarate dependent dioxygenase (FTO), insulin like growth factor 2 mRNA binding protein 1 (IGF2BP1), YTH domain containing 1 (YTHDC1), YTHDC12, YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), THDF2, YTHDF3, NOP2/Sun RNA methyltransferase family member 7 (NSUN7), NOP2/Sun RNA methyltransferase 2 (NSUN2), NSUN3, NSUN4, NSUN5, NSUN6, tRNA aspartic acid methyltransferase 1 (TRDMT1), DNA methyltransferase 1 (DNMT1), DNMT3, DNA methyltransferase 3 alpha (DNMT3A), DNMT3B, NOP2 nucleolar protein (NOP2), tet methylcytosine dioxygenase 2 (TET2), tRNA methyltransferase 6 non-catalytic subunit (TRMT6), Aly/REF export factor (ALYREF), tRNA methyltransferase 61A (TRMT61A), TRMT61B, ALKBH1 , and ALKBH3 .Modification of RNA methylation, including m6A (N6-methyladenosine), m5C (methyl-5-cytosine), and m1A (N1-methyladenosine), have been shown to influence RNA function . ExpressFDX1 expression and survival in pan-cancer.Kaplan-Meier (KM) and univariate Cox regression analyses were performed to evaluate the overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) of patients from the TCGA database. Univariate Cox regression analysis was conducted using the R packages “survival” and “forestplot” to assess the relationship between MLH1), mutS homolog 2 (MSH2), MSH3, MSH4, MSH5, MSH6, PMS1 homolog 1, mismatch repair system component (PMS1), and PMS2 in different cancers and to evaluate the correlation between these gene levels and FDX1 expression. MSI scores were determined for samples in pan-cancer based on somatic mutation data downloaded from the TCGA database. Data of varscan2 variant aggregation and masking was downloaded from the UCSC Xena database and used a Perl script to calculate TMB scores. Spearman’s rank correlation coefficient was used to analyze the relationship of FDX1 expression with that of MMR gene, MSI, and TMB.TCGA expression profile data were used to assess the level of MMR gene expression, including mutL homolog 1  and used CIBERSORT to calculate the relative scores for 22 immune cells in pan-cancer. Spearman’s rank correlation coefficient was used to analyze the correlation between FDX1 levels and the infiltration level of each immune cell in cancer. In addition, we explored the association between FDX1 expression and immune-related genes, which are chemokine, chemokine receptor, major histocompatibility complex (MHC), immunosuppressive, immunostimulatory, and immune checkpoint-related genes, in pan-cancer, using the the R package “limma.” The “reshape2” and “RColorBrewer” packages were used to visualize the results.The relationship between FDX1 mRNA expression was evaluated. We performed drug screening data using the GSCA database, which integrated over 10,000 genomic data in pan-cancer from TCGA and over 750 small-molecule drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) database.The relationship between drug sensitivity and FDX1 in cancer cells at the single-cell level, we downloaded the relevant data from the CancerSEA database and created a heatmap. Furthermore, the t-SNE diagrams of all individual cells were also obtained from CancerSEA.To validate the different functions of FDX1 across the pan-cancer. The Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets were downloaded from the GSEA website (https://www.gsea-msigdb.org/gsea/downloads.jsp) and used the R packages “limma,” “org.Hs.eg.db,” “clusterProfiler,” and “enrichplot” to investigate the functions of FDX1. We used the String database to create an interaction network for FDX1. A protein was considered to interact with FDX1 in the network if its interaction score exceeded 0.4. Active interaction sources included text mining, experiments, databases, co-expression, neighborhood, gene fusion, and co-occurrence.Gene Set Enrichment Analysis (GSEA) was conducted to explore the biological functions of 2 at 37 °C. Elesclomol  was diluted in a cell culture medium at 100 nmol/L concentration.The immortalized normal human urothelial cell line SV-HUC-1 and human bladder urothelial carcinoma (BLCA) cell lines T24 and 5637, and human proximal tubular epithelial cell line HK-2 and human clear cell renal cell carcinoma (ccRCC) cell lines 786-O and caki-1, and human normal prostatic epithelial cells RWPE-1 and human prostate cancer (PCa) cell lines PC-3 and DU145 were all purchased from Procell Life Science and Technology Co., Ltd. . SV-HUC-1 and PC-3 cells were cultured in Ham’s F-12K medium (Procell) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. T24, HK-2, caki-1, and DU145 cells were cultured in DMEM medium (Procell) supplemented with 10% FBS and 1% penicillin/streptomycin. RWPE-1 cells were cultured in complete medium of human prostatic epithelial cells (Procell). Furthermore, 5637 and 786-O cells were cultured in RPMI 1640 medium (Procell) supplemented with 10% FBS and 1% penicillin/streptomycin. All the cell lines were cultured in an incubator with 5% COFDX1 using Green qPCR SuperMix (TransGen Biotechnology). The specific primers in our study were as follows: FDX1, F-5′-CGATGGCATCAAGGTCTTTCCC-3′, and R-5′-CAGCAGGAGTTTCATGCGGAAC-3′; β-Actin, F-5′-GACGTGGACATCCGCAAAG-3′, and R-5′-CTGGAAGGTGGACAGCGAGG-3′. Finally, the relative expression of FDX1 was calculated using the 2−ΔΔCT method.Total RNA from mentioned above cell lines was isolated using the TransZol Up Plus RNA kit . RNA concentration was measured using NanoDrop 2000 . Next, cDNA was obtained using reverse transcription (RT). Finally, RT-quantitative polymerase chain reaction (qPCR) was conducted to investigate the expression of Whole-cell lysates were extracted using RIPA buffer  supplemented with a protease inhibitor cocktail . The protein concentration was measured using a BCA protein assay kit . Cell lysates were performed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and the protein bands were electrophoretically transferred onto PVDF membranes. Subsequently, non-specific antigen binding was blocked using 5% skim milk. The membranes were incubated at 4°C overnight with primary antibodies . Membranes were incubated the next day with 1:5,000-diluted secondary antibodies at room temperature for 1 h (Proteintech Group). Enhanced chemiluminescence was used to visualize the image (Proteintech Group). Antibody against β-actin was used as an internal reference (Proteintech Group).After treatment with elesclomol for 16 h, the cells were transferred to 96-well plates (100 μL cell suspension per well) at a density of 3,000 cells/well in triplicate for each group and were incubated in a humidified incubator. CCK-8 reagent (Transgene Biotech) was added to each well, and the cells were incubated for an additional hour. A microplate reader  was used to measure the absorbance  at 450 nm. OD values were measured at 0, 24, 48, and 72 h.2 for 16 h. Next, the cells were washed twice with fresh medium and caspase3/7 activity detection reagent working solution added to each well at a concentration of 1 μl/ml. After incubating at 37°C and 5% CO2 for 30 min, fluorescence was measured using a microplate reader (Biotek Gen5).Caspase3/7 activity of the cells was measured using a caspase3/7 live-cell fluorescence real-time detection kit  according to the manufacturer’s protocol. Cells were treated with elesclomol and incubated at 37°C and 5% COp < 0.05 was considered significant. Comparison of difference between adjacent normal and tumor tissues used Wilcoxon test; p < 0.05 indicated the statistical significance. The Kaplan-Meier curves and univariate Cox proportional hazard regression models were used for all survival analyses. Statistical analyses of the bioinformatics results were performed using R software (Version 4.1.2). The statistical significance of the in vitro data was determined using GraphPad Prism .All gene expression data were normalized using a log2 transformation. The correlation analysis between the two variables used Spearman’s or Pearson’s test; FDX1 expression in various cancer types, we first analyzed its expression in 33 cancers using TCGA data. Excluding those cancers without corresponding normal samples, significant differences in FDX1 expression were found between tumor and normal tissues in 17 types of cancer. FDX1 was lowly expressed in breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pheochromocytoma, and paraganglioma (PCPG), rectum adenocarcinoma (READ), sarcoma (SARC), and thyroid carcinoma (THCA), while highly expressed in glioblastoma multiforme (GBM), stomach adenocarcinoma (STAD), and uterine corpus endometrial carcinoma (UCEC)  . Due to or types . Moreovedatabase .FDX1 expression at the protein level, we analyzed the results provided in the HPA database. As shown in FDX1 displayed weak-to-moderate cytoplasmic positivity in thyroid cancer, colorectal cancer, liver cancer, and melanoma. Furthermore, normal liver tissues did not reveal FDX1 staining, while tumor liver tissues showed moderate staining. Normal breast and lung tissues, and lung and breast tumor tissues did not detect with FDX1 staining. We also analyzed the subcellular location of FDX1 in the HPA database. The protein of FDX1 was mainly localized to the mitochondria and was enhanced in cell lines of A-431 (human epidermoid carcinoma cells), U-2 OS (human osteosarcoma cells), U-251 MG (human glioma cells), and particularly in CACO-2   . Taken tFDX1 using the GSCA database. Our data revealed a correlation between FDX1 expression and DNA methylation in 13 tumors . Likewise, FDX1 expression was positively correlated with NSUN6 levels in 10 tumors, except for GBM, KIRC, KIRP, brain lower grade glioma (LGG), and ovarian serous cystadenocarcinoma (OV). In addition, FDX1 expression was positively correlated with YTHDF1 in 11 tumors but not in BRCA, KIRP, LIHC, and LUAD , GBM, HNSC, LIHC, LUAD, LUSC, and PCPG and correlated positively in skin cutaneous melanoma (SKCM). Contrasting results were found for the expression of TRMT6, which was positively correlated with FDX1 expression in 14 tumors, but not in KIRP, LIHC, and TGCT. These results show that the altered epigenetic status of FDX1 may contribute to tumorigenesis.Modification of RNA methylation, including m6A, m5C, and m1A, results in different outcomes that influence RNA functions and may contribute to tumorigenesis . We, theand LUAD . As showFDX1 expression in pan-cancer, including OS, DSS, DFI, and PFI analyses based on the TCGA database. Analysis of OS by Cox regression indicated that high expression of FDX1 was associated with longer survival times in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and KIRC, but not in HNSC and LGG , HNSC, LGG, and pancreatic adenocarcinoma (PAAD) and was a protective factor for patients with COAD, KIRC, and SKCM  and HLA-DMB (an HLA-related gene) was positively correlated with FDX1 expression in 13 tumors, excluding THCA  and HAVCR2 (an immune checkpoint inhibitor-related gene) in BRCA, GBM, HNSC, LGG, LUSC, SARC, SKCM, TGCT, and UCEC. In contrast, FDX1 expression was negatively correlated with CD40 expression in ACC, COAD, ESCA, KICH, KIRC, KIRP, acute myeloid leukemia (LAML), PRAD, STAD, and THCA, but was positively related to this gene expression in the other six cancers . In contrast, the invasion functional state of OV was significantly negatively correlated with FDX1 expression. FDX1 expression profiles are shown in single cells of AML, OV, and RCC using a T-SNE diagram , iron-sulfur cluster assembly enzyme (ISCU), and iron-sulfur cluster assembly 1 (ISCA1) and cytochrome P450 proteins such as cytochrome P450 family 11 subfamily A member 1 (CYP11A1) and cytochrome P450 family 11 subfamily B member 2 (CYP11B2).We created a PPI network for FDX1 in BLCA, ccRCC, and PCa cell lines. As shown in FDX1 was detected in T24 and 5637 cells than in SV-HUC-1 cells. FDX1 was highly expressed in PC-3 and DU145 cells than in RWPE-1 cells. In contrast, FDX1 has low expression in 786-O and caki-1 cells than in HK-2 cells. According to the previous research (FDX1 and promoted copper-dependent cell death. Thus, we performed a CCK-8 assay to evaluate the effect of elesclomol on BLCA, ccRCC, and PCa cells proliferation. The CCK-8 assay showed that the cell viability of the elesclomol treatment group was markedly lower than that of the control group (FDX1 was detected in the elesclomol treatment group (FDX1 is downregulated by elesclomol, inhibiting cell viability in vitro, without activating caspases 3 and 7.To verify the results of the above analysis, we firstly examined the expression of research , elesclool group . Moreovent group . We furtnt group . These rFDX1 was closely related to the occurrence and development of various tumors (FDX1 has not mainly been elucidated in cancer, and its role in tumorigenesis or pan-cancer is still unclear. Therefore, in our study, we conducted a pan-cancer analysis of FDX1 in different cancers based on the data from the most comprehensive databases and also explored the effect of FDX1 in BLCA, ccRCC, and PCa cells for the first time.The pan-cancer analysis provides a comprehensive understanding of the molecular aberrations and functional roles across various cancers. It helps to identify new diagnostic biomarkers and new therapeutic targets for cancers . FDX1 fus tumors . HoweverFDX1 in pan-cancer. Our results showed that FDX1 was dysregulated in 17 types of cancer, and IHC analysis confirmed this tendency at the protein level in thyroid cancer, colorectal cancer, and liver cancer. Our research reached the opposite result to previous studies when we used only TCGA database analysis. However, when we analyzed by combining TCGA and GTEx databases, we drew identical results to those of previous research (FDX1 neither inhibited tumor cell growth nor induced apoptosis but inhibited the ATP production and fatty acid oxidation in LUAD cells (FDX1 in human breast cancer and lung adenocarcinoma cells, inhibits FDX1-mediated Fe-S cluster biosynthesis, and promotes copper-dependent cell death (FDX1 mRNA expression and its protein expression are not completely consistent, which may be due to temporal and spatial gaps between the transcription and translation in eukaryotic gene expression. Meanwhile, there are many modifications in transcriptional and post-translational, as supported by previous research (FDX1 was correlated with better prognosis in KIRC, THCA, and LIHC but was the opposite in ACC, HNSC, LGG, and PAAD. These findings demonstrated that FDX1 could be used as a biomarker of the prognosis for various cancers.We first assessed the expression and prognostic significance of research . For exaAD cells . FDX1 isAD cells . Elescloll death . This diresearch . NotablyFDX1 expression was significantly correlated with DNA methylation in six tumors, with positive correlations in BRCA, KIRP, LIHC, and LUSC but negative correlations in BLCA and KIRC. Furthermore, in most cancers, FDX1 expression was significantly positively correlated with m6A-, m5C-, and m1A-related genes, such as YTHDF1, YTHDF2, TRMT10C, and NSUN6. These findings suggest that the changes in the epigenetic status of FDX1 may contribute to tumorigenesis. Tumors with defects in the MMR system will cause high levels of MSI, which leads to the aggravation of TMB and results in tumor occurrence (FDX1 expression was highly correlated with MMR gene, MSI, and TMB in most cancers. These results showed the function of FDX1 in mediating tumorigenesis by regulating DNA and RNA methylation, MMR gene, MSI, and TMB, which was consistent with the previous studies (Both DNA methylation alterations and RNA methylation modification play crucial roles in tumorigenesis . Our stucurrence . Our res studies .FDX1 is also strongly involved in cancer immunity. TME plays a decisive role in tumor initiation, progression, and response to therapies (FDX1 expression and stromal and immune cell content in the TME of ACC, KIRC, STAD, and THCA, but not in LGG and SARC. Tumor-infiltrating immune cells contribute significantly to the homeostasis of TME and play a vital role in the occurrence, development, and immunotherapy of tumors (FDX1 had a negative relationship with NK cells activated in most cancers. This finding may explain the risk role of FDX1 in most tumor types. Furthermore, our study also revealed the co-expression of FDX1 with immune-related genes, including chemokine, chemokine receptor, MHC, immunostimulatory, immunosuppressive, and immune checkpoint-related genes. FDX1 expression is closely correlated with almost all immune-related genes and contributes to tumor development (FDX1 expression may be a promising strategy to increase the efficacy of immunotherapy.Our results showed that herapies . Accordif tumors . As membf tumors . Our datelopment . OverallFDX1 expression and IC50 of over 750 anticancer drugs. The results suggested that FDX1 expression was closely related to sensitivity of many drugs, but high expression of FDX1 reduced the sensitivity to 17-AAG and CHIR-99021. This phenomenon means that its potential role in drug resistance requires further research. However, we reached the opposite result to a previous study, in which elesclomol could directly target FDX1 and promote copper-induced cell death in human rhabdomyosarcoma and LUAD cells (FDX1 in copper-induced cell death requires further investigation.Mounting evidence demonstrated that some new advances had been made in cancer treatment, such as RNA interference , targetiAD cells . This diFDX1 in pan-cancer specifically. The PPI network showed that FDX1 interacted with HSCB, ISCU, ISCA1, CYP11A1, and CYP11B2, all associated with the mitochondrial respiratory chain. The results based on the CancerSEA database showed that FDX1 is closely related to differentiation, proliferation, stemness, and invasion at the single-cell level in most cancers. Consistent with our data, FDX1 was previously reported to be involved in cell proliferation (FDX1 can inhibit copper-induced cell death in LUAD cell lines without the involvement of apoptosis-related genes (FDX1 was significantly correlated with the pathway of pentose and glucuronate interconversions, cytokine-cytokine receptor interaction, and regulation of autophagy. Supporting that, FDX1 also plays a vital role in glucose metabolism (Next, we used the PPI network, the CancerSEA database, and GSEA analysis to address the function of feration  and thused genes . The KEGtabolism , promotiin vitro experiments to investigate the effect of FDX1 on BLCA, ccRCC, and PCa cells. These analyses demonstrated a relatively higher expression of FDX1 in BLCA and PCa cell lines and low expression in ccRCC cells, consistent with our bioinformatic analytical result. In addition, elesclomol inhibited cell viability in vitro without activating caspases 3 and 7 and decreased the expression of FDX1, which was consistent with findings of a previous study (FDX1 is downregulated by elesclomol, which inhibited BLCA, ccRCC, and PCa cells viability in vitro without activating caspases 3 and 7.Furthermore, we performed a series of us study . These rFDX1 further using a larger sample size. Second, our findings suggested that FDX1 can serve as a prognostic factor for different tumors, which requires further verification. Third, the effects of FDX1 on the tumor microenvironment and immunotherapy required experimental and clinical validation. Fourth, although we confirmed that elesclomol targeted FDX1 and inhibited cell viability of BLCA, ccRCC, and PCa cells, the precise regulatory mechanisms remain unclear and require further exploration.Our study had several limitations. First, some contradictory findings regarding individual cancers were observed in our study. Therefore, it is necessary to investigate the expression and function of FDX1 indicated that this factor was differentially expressed between tumor and normal tissues and revealed correlations between FDX1 expression and DNA methylation and RNA methylation-related genes. Our findings suggested that FDX1 may be a prognostic factor for different tumors. Moreover, FDX1 expression was associated with MMR gene, MSI, TMB, and immune cell infiltration in different cancer types. Its impact on tumor immunity and drug sensitivity also varied with tumor types. Importantly, elesclomol targeted FDX1 and inhibited cell viability in BLCA, ccRCC, and PCa cells. These findings may help clarify the role of FDX1 in tumorigenesis and development and provide a reference for more accurate and personalized immunotherapy in the future.In summary, our first pan-cancer analysis of


DNA methylation represents a crucial mechanism of epigenetic regulation in hematologic malignancies. The methylation process is controlled by specific DNA methyl transferases and other regulators, which are often affected by genetic alterations. Global hypomethylation and hypermethylation of tumor suppressor genes are associated with hematologic cancer development and progression. Several epi-drugs have been successfully implicated in the treatment of hematologic malignancies, including the hypomethylating agents (HMAs) decitabine and azacytidine. However, combinations with other treatment modalities and the discovery of new molecules are still the subject of research to increase sensitivity to anti-cancer therapies and improve patient outcomes. In this review, we summarized the main functions of DNA methylation regulators and genetic events leading to changes in methylation landscapes. We provide current knowledge about target genes with aberrant methylation levels in leukemias, myelodysplastic syndromes, and malignant lymphomas. Moreover, we provide an overview of the clinical trials, focused mainly on the combined therapy of HMAs with other treatments and its impact on adverse events, treatment efficacy, and survival rates among hematologic cancer patients. In the era of precision medicine, a transition from genes to their regulation opens up the possibility of an epigenetic-based approach as a diagnostic, prognostic, and therapeutic tool. Hematologic malignancies form a heterogeneous group of acute and chronic diseases, clonally expanding into the blood, bone marrow, and lymph nodes. Due to their highly aggressive manner, blood cancers are characterized by rapid progress, affecting both pediatric and adult patients. Improved treatment response and outcomes have been documented in pediatric patients, who achieve remission in the overwhelming majority. Genetic and epigenetic changes lead to the clonal proliferation of stem and progenitor cells. Alterations in downstream signaling pathways contribute to the disruption of the self-renewal ability of hematopoietic cells and their differentiation into other lineages.Although epigenetic mechanisms have been largely evaluated in embryonic development, differentiation, and organogenesis ,2, mountDNA methylation plays a critical role in hematopoiesis and hematopoietic stem cell differentiation and proliferation . EpigeneIn this review, we provide current data focusing on the emerging role of DNA methylation-related changes in hematologic malignancies, including leukemias, myelodysplastic syndromes, and lymphomas. The studies concerning the aberrant expression of DNA methylation enzymes and target genes are analyzed. Moreover, we will discuss the therapeutic implication of DNA methylation status and provide an overview of the clinical trials, evaluating the clinical significance of DNA methylation mechanisms in hematological malignancies.DNMT genes are known in the human genome, including DNMT1, DNMT2, DNMT3A, DNMT3B, and DNMT3L, but only de novo DNMT3A, DNMT3B, and DNMT1 have a catalytic domain with methylation activity. There was much evidence proving that the regulation of DNA methylation by DNMTs is critical for normal hematopoiesis [The process of DNA methylation is catalyzed by enzymes called DNA methyltransferases (DNMTs) that transfer a methyl group from S-adenosine methionine (SAM) to the fifth carbon of a cytosine. Five opoiesis . Changesopoiesis .p15(INAK4B) expressed higher levels of DNMT1 and DNMT3B [DNMT1 gene have been detected in AML cells [During normal hematopoiesis, DNMT1 has an essential role in hematopoietic stem cell (HSC) self-renewal and multilineage hematopoietic differentiation, because the lack of DNMT1 in HSCs leads to a reduction in myeloid lineages compared to lymphoid lineages . Togethed DNMT3B . Overexpd DNMT3B ,14,15. NML cells .DNMT3B gene are found in human hematological malignancies, the role of DNMT3B was well documented in mouse hematopoiesis.Since DNMT1 represents one of the key methylation regulators, it could serve as a potential therapeutic target for lymphoid and myeloid malignancies. In chronic myeloid leukemia (CML), aberrant DNA hypermethylation contributes to low tyrosine kinase inhibitor (TKI) sensitivity and the persistence of leukemic stem cells (LSCs). Targeting DNMT1-mediated aberrant DNA hypermethylation using OR21  showed anti-tumor activity and impaired LSCs, suggesting it is a potential therapeutic target for CML . DNMT3a +/− mice developed T-cell lymphomas, chronic lymphocytic leukemia (CLL), and myeloproliferative disorders. Dnmt3b+/CI  and Dnmt3bCI/CI mice were affected by B-cell rather than T-cell malignancies. These observations could suggest that Dnmt3b is critical to prevent B-cell transformation in vivo [Lopusna et al. observed that 43% of Dnmt3b in vivo . Moreove in vivo . However in vivo . As docu in vivo .DNMT3A mutations has been reported, mainly in patients with AML [DNMT3A hot-spot mutation R882H was observed in up to 60% of AML [DNMT3A mutation R882H, suggesting that this mechanism could precede AML. As noted, CpG island hypermethylation in patients with wild-type DNMT3A did not correlate with gene silencing. According to the authors, DNMT3A-mediated hypermethylation might be a consequence of AML progression [DNMT3A mutations in AML patients are associated with shorter overall survival (OS) and predict an improved outcome with high-dose induction chemotherapy, representing a promising prognostic and predictive tool [In hematopoietic disorders and malignancies, a high prevalence of with AML ,22. Somawith AML ,24. The % of AML ,25, 18% % of AML , and 10%% of AML . This algression . Importaive tool ,30.TET1 and TET3 genetic changes are very rare in leukemia. However, TET2 is one of the most mutated genes in AML, chronic myelomonocytic leukemia (CMML), and MDS [TET2 was detected, suggesting a low mutation rate in DLBCL patients [TET2 expression had markedly shorter OS in both non-M3 (hypergranular AML) and cytogenetically normal AML (CN-AML), with a significant correlation between TET2 expression and OS in CN-AML patients [TET1 and found alternative mechanisms of TET1 inactivation in human B-cell non-Hodgkin lymphomas (NHL) [TET1 expression was independently associated with poor OS and complete remission (CR) in CN-AML patients [TET enzymes represent DNA demethylation regulators, which are involved in the removal of methyl marks from DNA and play a role in hematopoietic differentiation.  and MDS . In a copatients . Patientpatients . Cimminoas (NHL) . In contpatients .IDH1, IDH2, and TET2 with frequencies of 6.2%, 8.6%, and 7.3%, respectively [IDH1/2 mutations. AML cells with mutations in TET2 or IDH1/2 displayed hypermethylation, suggesting its important function in hematopoietic cells among AML patients [IDH1/2 mutations in T-cell acute lymphoblastic leukemia (T-ALL) are poorly reported. Simonin et al. provided the first analysis of the oncogenetic landscape of IDH1/2 mutations in 1085 T-ALL patients. The results showed that almost 4% of IDH1/2 mutations correlated with poor prognosis [IDH1/2 are enzymes that convert isocitrate to α-ketoglutarate, which could serve as a substrate for other enzymes, e.g., TET2. In a study on AML patient cohort, high-throughput resequencing revealed genetic alterations in ectively . As notepatients . In contrognosis .WT1), were reported to increase methylation in AML patients. CEBPA physically interacts with DNMT3A, and the N321D mutation in CEBPA decreases the DNA-binding ability of DNMT3. Furthermore, CEBPA mutations are responsible for promoter hypermethylation of various genes, including Polycomb Repression Complex (PCR2) target genes active in histone H3 methylation [Additionally, other regulators of DNA hypermethylation, including CCAAT/enhancer binding protein α (CEBPA) and Wilms tumor protein 1 , and frequency of CR [ERα, OLIG2, ITGBL1, SCIN, DLX5, MSH2, RAD50, and SOCS1 genes [Promoters of many tumor suppressor genes (TSGs) are most commonly inhibited by methylation. Cyclin-dependent kinase inhibitors cy of CR ,46,47. IS1 genes ,52,53.DOK1 and DOK2 genes was associated with lower OS [DOK6 gene was found in AML patients, but with the opposite effect on OS [C1R and DNA repair genes MLH1 and RAD51 [The DOK protein family, characterized as phosphotyrosine adapters with several functions in cell biology, is commonly expressed in myeloid cells. In a study comprising AML patients, He et al. observed that hypermethylation-mediated decreased expression of lower OS . Similarct on OS . Longer nd RAD51 ,56.CEBPA, PBX3, LZTS2, and NRGA1 serves as a predictor for longer survival [GPX3 and DLX4 correlated with a favorable treatment impact, which is in contrast to previously reported studies documenting their correlation with lower OS [Sestakova et al. performed an extensive validation study for 27 genes from 14 studies to verify the predictive role of aberrant DNA methylation in AML. The results showed that hypermethylation of survival . In addilower OS ,59.RUNX1-mutated AML cohort identified 51 differential methylated genes. As shown, the changes in expression profiles were found in ten of them. Hypermethylation of CD96, LTK, and MS4A3 correlated with poor prognosis, which could be related to their effects on cell cycle regulation and differentiation [SOX7, TCF21, CTNNA1, and CAMK4, as well as hypomethylation of DDX43, LZTS2, or NRGA1, was observed in MDS/AML patients. Due to the lack of prognostic potential in numerous studies, complex evaluation requires further investigation [In some cases, mutations in important transcription factors can lead to alterations in epigenetic modifications. Genetic changes in Runt-related transcription factor 1 (RUNX1), a key player in hematopoiesis, led to aberrant methylation in target genes. The study on the ntiation . Higher tigation ,64,65,66CML is characterized by the presence of translocation-creating oncoprotein BCR-ABL1, and the development of this disease consists of three phases, namely, the chronic phase (CP), accelerated phase (AP), and blast crisis phase (BP) . The higABL1, CDH3, and NPM2 presented the highest methylation in all phases of CML. Furthermore, increased methylation of CDKN2B (p15), OSCP1, PGRA, PGRB, and TFAP2E genes was described during CML progression [ABL1, WT1, ZNF577, and hypomethylation of G6B and TRIM15 [DDX43 represents a frequently overexpressed gene in hematological malignancies. Epigenetic regulation of DDX43 by promoter methylation and a negative correlation between hypomethylation and higher expression of DDX43 was observed in CML patients. Moreover, the frequency of DDX43 hypomethylation increased in CP, AP, and BP by 23.4%, 25.0%, and 33.3%, respectively [Jelinek et al. observed that among 10 selected genes analyzed by pyrosequencing, gression . Anotherd TRIM15 . DDX43 rectively .HOXA4 and HOXA5 were hypermethylated in CML patients, and the presence of promoter methylation correlated with resistance to imatinib, belonging to a group of TKIs. Patients with HOXA4 and HOXA5 methylation levels higher than 63% showed 3.78- and 3.95-times-higher risk for imatinib resistance, respectively [OSCP1 and NPM2 genes [PLCD1, DLX4, DDIT3, PU.1, DAPK1, BIM, and GPX3, could represent potential prognostic or therapeutic targets in CML [SHP-1 and relevant protein expression was associated with the presence of promoter methylation in advanced CML patients. SHP-1, a protein tyrosine phosphatase, is expressed mainly in HSC and plays a critical role in the regulation of JAK/STAT and MYC, AKT, and MAPK pathways. Alterations in SHP-1 methylation status could lead to the deregulation of included pathways and blastic transformation in CML patients [Promoter hypermethylation is mostly associated with TSGs involved in crucial cell functions, including the regulation of differentiation, proliferation, apoptosis, cell cycle, and growth. Similar to AML, ectively . ImatiniM2 genes . Aberrans in CML ,76,77,78patients .CDKN2B (p15) presented decreased expression in most T-ALL cases, originating from deletion and promoter hypermethylation. CDKN2B hypermethylation frequently occurred together with mutations in DNMT3A and NRAS genes. In addition to the association with an older age of onset, the results showed a relatively early presence of T-cell precursors of ALL, causing the quick arrest of T-cell differentiation [DLX3, belonging to the DLX gene family with a wide range of functions during hematopoiesis, could be active in the resistance to apoptosis. In pediatric B-cell ALL, Campo Dell Orto et al. observed aberrant methylation of DLX3 with reduced gene expression in patients with MLL-AF4 fusion, while no methylation was found in the subgroup with the TEL-AML1 fusion protein. The results suggested a potential role of DLX3 methylation in B-cell acute leukemias [RUNDC3B expression are typical for lymphoid but not myeloid malignancies [ALL represents hematological cancer of immature T or B cells. T-ALL and B-ALL represent approximately 15–20% and 85% of all cases, respectively . A genomntiation . DLX3, beukemias . Some epgnancies . RUNDC3Bgnancies .FOXE3 and TLX3 genes, showing their ability to discriminate between cancerous and healthy bone marrow samples with high specificity and sensitivity, which indicates their potential as diagnostic markers. Furthermore, TLX3 methylation correlated with minimal residual disease (MRD) in pediatric ALL patients [RASSF6 and RASSF10 genes were frequently methylated and associated with the MRD in peripheral blood samples of adult ALL patients. In addition, the hypermethylation of RASSF6 is significantly associated with shorter OS in precursor B-ALL patients [p21, WNT5A, Dkk-3, and NES1 genes with shorter disease-free survival (DFS) and OS [PCDH17 gene was frequently observed in both B-ALL and T-ALL with a relationship with lower OS and increased risk for relapse and death [Several specific methylation profiles were found to be diagnostic, prognostic, or therapeutic markers for ALL. Chatterton et al. monitored the methylation of patients . In B-ALpatients ,87. In a) and OS ,89,90,91nd death ,93.TWIST2 hypermethylation and its inactivation were observed in more than 50% of ALL patients and 91% of samples from relapsed patients. In vitro experiments showed that the re-expression of TWIST2 increased apoptosis and sensitivity to chemotherapeutics [ADAMTSL5 (93% vs. 38%) and CDH11 (79% vs. 40%) in chemo-resistant vs. chemo-sensitive patients, respectively [ASNS gene in T-ALL childhood patients was associated with poor outcomes and resistance to asparaginase, which is a high-dose drug involved in T-ALL therapy [Importantly, the specific gene methylation profiles can represent a predictive therapeutic marker because aberrant methylation can be responsible for chemotherapeutic resistance. apeutics . A compaectively . On the  therapy .HOX gene clusters [TWIST2, DAPK1, SLIT2, or ZAP70 [ZAP70 predicts poor outcomes for CLL patients, and CpG sites important for the regulation of transcription were identified in the 5’ regulatory region. According to these findings, a decreased methylation level in this specific CpG dinucleotide is a predictive biomarker for poor prognosis [WIF1, DKK3, APC, SFRP1, SFRP2, SFRP4, and SFRP5 was observed in the peripheral blood of CLL patients. However, no association between methylation and clinical parameters was confirmed [CLL belongs to the most common leukemias in the adult population, characterized by the clonal expansion of malignant B cells . Similarclusters . Previouor ZAP70 ,101,102.onfirmed ,104.ET-1 expression in CLL. The unmethylated ET-1 gene was observed in healthy donors, while CLL patient samples exhibited 32% unmethylated and 68% methylated profiles. As shown, high methylation of the first ET-1 intron decreased its expression, suggesting the importance of epigenetic regulation [ANGPT2 correlated with increased expression and are associated with shorter OS and poor prognosis in CLL patients [PAX9, DUSP22, RPRM, SASH1, and CRY1 [CRY1 promoter inactivated its expression and was associated with better outcomes [SHANK1 positively correlated with the absolute lymphocyte count. Increased SHANK1 methylation was found in samples during the pre-CLL diagnosis period, suggesting that epigenetic modification of SHANK1 occurred early in CLL carcinogenesis [SHANK1, the NFATC1 gene belongs to the most hypomethylated genes identified in CLL. A decreased methylation level is strongly associated with NFATC1 upregulation, resulting in the deregulation of target gene expression. Inactivation of NFAT regulator calcineurin by ibrutinib increased apoptosis in leukemic cells. Thus, NFACT1 might represent a potential therapeutic target in CLL diagnosis [The hormone peptide Endothelin-1 (ET-1) plays a role in various cell functions, including proliferation. Microenvironment stimuli activated downstream receptors, leading to increased gulation . The sampatients . The proand CRY1 ,108,109.ogenesis . In compiagnosis .(Ig) genes. The Ig heavy chain variable region (IGHV) with high mutational prevalence (IGHV-M) correlated with a more favorable prognosis compared to IGHV unmutated (IGHV-UM) CLL patients [VHL and ABI3, acting as TSGs, were preferentially methylated and correlated with decreasing expression [WNT5A distinguished patients with worse outcomes in the IGHV-M subgroup. Reduced WNT5A expression through hypermethylation preferentially in three CpG dinucleotides within the regulatory region correlated with good prognoses [Two subgroups of CLL patients are classified according to the presence of somatic mutations in immunoglobulin patients . In the pression . In contrognoses .RASSF1A, p16INK4a, p18INK4c, p15INK4b, SYK, BOB.1/OBF.1, and CD79B [Malignant lymphomas (MLs) represent a heterogeneous group of hematologic malignancies in primary or secondary lymphatic organs arising from various types of B and T lymphocytes or NK cells. Generally, MLs cover classical Hodgkin lymphomas (HL) and diverse groups of NHL . Pathogend CD79B ,117,118.nd CD79B .DSP, FZD8, KCNH2, and PPP1R14A exhibited promoter methylation in 28%, 67%, 22%, and 78%, respectively. In addition, the highest methylation level after treatment with demethylating agents was detected in LRP12 and CDH1 genes, presenting 94% and 92%, respectively [SIRT1 and increased KLF4, DAPK1, and SPG20 gene methylation levels. In vitro analysis revealed that DNMT1 did not affect hypermethylation maintenance of KLF4, DAPK1, and SPG20 genes [Bethge et al. identified 233 downregulated genes in a cohort of B-cell NHL patients. From the analyzed gene panel, ectively ,121. Ano20 genes ,123.p16/CDKN2A, p21/CDKN1A, and p27/CDKN1B [p16 methylation higher than 5%. According to the results, patients younger than 65 years manifested better progression-free survival (PFS) when the p16 methylation level reached more than 25% [p57/KIP2, suggested that epigenetic modification of p57 could be established as a biomarker for MRD in DLBCL [RUNX3, DAPK1, and MT16, represent prognostic factors for DFS. Moreover, hypermethylation of RUNX3 and CDH1 was shown to be an independent prognostic factor for OS [Most DNA methylation studies have been performed in NHL, specifically in DLBCL . The res7/CDKN1B . Howeverthan 25% . Aberranin DLBCL . Shawky r for OS .CDH23 and PCDH10 hypermethylation and downregulated expression with worse outcomes in DLBCL patients. As noted, methylation of these genes could serve as a risk marker or a potential therapeutic target [DAPK1 gene showing higher methylation significantly associated with lower OS, disease-specific survival, and 5- year survival in the DLBCL patient cohort [DAPK1 methylation in plasma samples was revealed in DLBCL. Patients with decreased methylation levels survived longer than patients with unchanged or regained DAPK1 methylation [SLIT2, DUSP4, and MGMT [SMAD1 was a critical player. In a clinical trial on DLBCL patients, treatment with azacitidine followed by chemoimmunotherapy showed demethylation of SMAD1 and increased chemosensitivity [Promoter methylation analysis of genes coding cadherins and protocadherins uncovered the association of c target ,129. Sevt cohort ,131. In hylation . Specifiand MGMT ,134,135.sitivity .Both global hypomethylation and specific promoter hypermethylation, primarily leading to the downregulation of TSGs, are important players in hematologic malignancies. Clinical investigations focused on drugs reversing altered epigenetic events, namely, epi-drugs. Two different types of DNMT inhibitors (DNMTi) represent analogs of nucleoside and non-nucleoside agents. Hypomethylating agents (HMAs) derived from cytidine, namely azacitidine and decitabine, were approved by the FDA for AML and MDS treatment . GuadeciIn addition, the novel molecule GSK368503 was identified for the potential reversible and selective inactivation of DNMT1 in preclinical models. The GSK3685032 molecule showed an increased anti-proliferative effect and presented less cytotoxicity compared to decitabine (80% vs. 29% for the negative growth death index) in 51 cell lines derived from leukemia, lymphoma, and multiple myeloma. The application of GSK3685032 resulted in robust DNA hypomethylation and activation of transcription, leading to better survival in mouse models .Mounting evidence documented that a combination of HMAs with chemotherapy, immunotherapy, or other treatment modalities can improve targeting, drug processing, and cytotoxicity .p = 0.1079). The survival rate was similar after an additional year, with a median OS in decitabine-intervened patients compared to controls at 7.7 and 5.0 months, respectively . Furthermore, PFS and response rates were more favorable for decitabine than for other treatments [p = 0.1009) [In the DACO-016 randomized phase III study for decitabine monotherapy, the median OS was 7.7 months in patients with AML treated with decitabine compared to the control arm with OS of 5.0 months (hazard ratio (HR), 0.85; 95% confidence interval (CI), 0.69–1.04; eatments . Accordi 0.1009) .p < 0.001) and relapse-free survival  compared to the placebo group. In addition, adverse effects associated with CC-486 treatment rarely required discontinuation and were successfully managed with a change of dose or using a medication, suggesting a safety profile of CC-486 therapy for AML [In addition to standard subcutaneous and intravenous application of decitabine and azacitidine, oral azacitidine (CC-486) intervention was approved as maintenance therapy. In phase III of the QUAZAR AML-001 study, CC-486 administration to older AML patients previously treated with chemotherapy presented significantly longer median OS , the differences were not statistically significant. Adverse events during treatment occurred mainly during the ten-day regimen [2). Moreover, 43% of relapsed or refractory MDS patients previously treated with HMAs achieved an overall response [In phase II of the dose-expansion study, patients with AML received 60 or 90 mg/m regimen . The res regimen . In the response .An overview of ongoing clinical trials focusing on the role of DNA methylation in leukemias and MDS, containing the study of decitabine/cedazuridine treatment with BMS-986253 in MDS patients, is shown in p < 0.001), respectively [Azacitidine pretreatment followed by high-dose chemotherapy with cytarabine and mitoxantrone showed an improved response rate in 61% of older AML patients with poor prognoses . Furtherectively . Treatmeectively ,150.An active anti-cancer response by specific T-lymphocytes was observed in MDS patients who received an intervention with decitabine and the NY-ESO-1 vaccine . HoweverNieto et al. studied a combination of azacitidine with high-dose chemotherapy  and stem-cell transplantation in refractory/relapsed lymphomas, presenting that event-free survival and OS rates for HL and DLBCL patients were 76% vs. 95% and 65% vs. 77%, respectively . SimilarOngoing clinical trials involving HMAs in combined therapy aim to determine the optimal therapy dose and synergy effect in the treatment of lymphoma patients .Current clinical oncology and cancer research aims to find new biomarkers for precise diagnosis and new targets for more efficient anti-cancer treatment modalities. Due to the aggressive nature of hematologic malignancies, early and correct diagnosis is the key to improving prognosis, treatment results, and patient survival. The highly toxic treatment negatively affects the entire organism and develops severe side effects.Enormous improvements in high-throughput sequencing methods and bioinformatic tools have helped to elucidate the impact of genetics and epigenetics on carcinogenesis. In addition to known genetic alterations, DNA methylation is one of the main epigenetic mechanisms that play a role in cancer initiation and progression. In the future, DNA methylation-based stratification of hematologic patients might lead to more personalized treatment with better outcomes. The reversibility of changes in DNA methylation landscapes enables broad clinical implications. However, adverse events associated with indiscriminate global hypomethylation with DNA methylation inhibitors are a matter of concern, and further investigations are highly warranted. According to the findings, DNA methylation processes in hematologic malignancies are usually associated with other mechanisms of epigenetic regulations, including histone modifications and miRNA regulation. Thus, evaluating the role of epigenetic modifications in a more complex matter would be beneficial for blood cancer patients.Mounting evidence from clinical trials highlights the potential of therapeutic strategies focusing on reversing aberrant DNA methylation patterns in hematological malignancies. Importantly, a combination of epi-drugs with chemo- or immunotherapy remains an emerging research area. Recent findings suggest that the DNA methylation-based approach sensitizes other anti-cancer treatment modalities and may improve the clinical outcomes for hematologic cancer patients.