Construction and Validation of a Novel Ferroptosis-Related Prognostic Model for Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.

Identification of U937JAK3-M511I Acute Myeloid Leukemia Cells as a Sensitive Model to JAK3 Inhibitor

Mutated JAK3 has been considered a promising target for cancer therapy. Activating mutations of JAK3 are observed in 3.9%–10% of acute myeloid leukemia (AML) patients, but it is unclear whether AML cells are sensitive to JAK3 inhibitors, and no disease-related human AML cell model has been reported. We have identified U937 as the first human AML cell line expressing the JAK3M511I activated mutation and confirmed that JAK3 inhibitors sensitively suppress the proliferation of U937 AML cells.

Frequency of Hematologic and Solid Malignancies in the Family History of Patients with Myeloid Neoplasms

Background: Studies demonstrated that there are several germline mutations that lead to a familial predisposition for acute myeloid leukemia and Myelodysplastic syndrome. According to the American Society of Clinical Oncology, the minimum cancer family history was defined as including first- and second-degree family history, type of primary cancer, and age at diagnosis. The current study aimed to estimate the frequency of positive family history for hematologic and solid malignancies in patients with Myeloid Neoplasms / Aplastic anemia. Patients and Methods: A cross-section study was carried out at the Center of Blood Diseases, Medical City Campus during the period from March-December 2020. A purposeful sample of all adult patients with Myeloid Neoplasms [Acute Myeloid Leukemia, Myelodysplastic Syndrome, Chronic Myeloid Leukemia, and Aplastic Anemia] was included in the study. A data collection form was prepared, based on the Hereditary Hematopoietic Malignancies Screening form adopted by the University of Chicago, and modified by the researchers; The data were collected by direct interview with the patients. Patients with hematologic malignancy and one or more first-degree relatives, or ≥2 second-degree relatives, with hematologic malignancies and individuals with Myelodysplastic Syndrome or Acute Myeloid Leukemia and two first or second-degree relatives with a diagnosis of solid tumor malignancy, were considered potential carriers of such genetic predisposition. Results: A total of 153 patients were included; males were nearly equal to females with a male to female ratio of nearly 1:1. Acute Myeloid Leukemia was found in 57.5%, Aplastic Anemia was found in 19%, Chronic Myeloid Leukemia in 17% and only four patients (6.5%) were known cases of Myelodysplastic Syndrome. Nine patients (5.9%) reported a family history of hematological malignancies, 29 (19.0%) reported a family history of solid malignancies and only one patient reported a family history of both hematological and solid malignancies. Regarding the official medical reports of the patients, no patient had been interviewed properly about this crucial point. Conclusion: Positive family history for hematological and solid malignancies in Iraqi patients with myeloid neoplasms is prevalent. Our current approach to this critical issue in Iraq needs to be re-considered.

A Predictor Combining Clinical and Genetic Factors for AML1-ETO Leukemia Patients

Core Binding Factor (CBF)-AML is one of the most common somatic mutations in acute myeloid leukemia (AML). t(8;21)/AML1-ETO-positive acute myeloid leukemia accounts for 5-10% of all AMLs. In this study, we consecutively included 254 AML1-ETO patients diagnosed and treated at our institute from December 2009 to March 2020, and evaluated molecular mutations by 185-gene NGS platform to explore genetic co-occurrences with clinical outcomes. Our results showed that high KIT VAF(≥15%) correlated with shortened overall survival compared to other cases with no KIT mutation (3-year OS rate 26.6% vs 59.0% vs 69.6%, HR 1.50, 95%CI 0.78-2.89, P=0.0005). However, no difference was found in patients’ OS whether they have KIT mutation in two or three sites. Additionally, we constructed a risk model by combining clinical and molecular factors; this model was validated in other independent cohorts. In summary, our study showed that c-kit other than any other mutations would influence the OS in AML1-ETO patients. A proposed predictor combining both clinical and genetic factors is applicable to prognostic prediction in AML1-ETO patients.

Comprehensive bioinformatic analysis of the expression and prognostic significance of TSC22D domain family genes in acute myeloid leukemia

Background: TSC22D domain family genes, including Tsc22d1-4, have been extensively reported to be involved in tumors. However, their expression profiles and prognostic significance in acute myeloid leukemia (AML) remain unknown. Methods: The present study investigated the expression profiles and prognostic significance of TSC22D domain family genes in AML through the use of multiple online databases, including the CCLE, EMBL-EBI, HPA, Oncomine,GEPIA2, UALCAN, BloodSpot, and GSCALite databases. The cBioPortal and GSCALite databases were used to explore the genetic alteration and copy number variation (CNV) of the Tsc22d3 gene. The TRRUST (Version 2) database was used to explore the gene ontology biological process, disease ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with the Tsc22d3 gene. The AnimalTFDB3.0, STRING, and Harmonizome databases were used to investigate the protein–protein interaction (PPI) network of the Tsc22d3 gene. The Harmonizome database was used for Tsc22d3 gene regulatory kinase analysis. The TargetScanHuman 7.2, MiRDB, and ENCORI databases were used to execute the analysis of the Tsc22d3 gene regulatory miRNAs. Then, the GSCALite and GEPIA2021 databases were used to investigate the correlation between Tsc22d3 expression and immune infiltration. Results: The expression of the Tsc22d3 gene was upregulated markedly in AML cells relative to normal hematopoietic stem cells. The expression of the Tsc22d3 gene was increased in AML tumor samples compared with healthy bone marrow samples. And overexpression of the Tsc22d3 gene was associated with poor OS in AML patients.This study implied that the Tsc22d3 gene is a new biomarker for predicting the prognosis of AML. Furthermore, gene ontology analysis showed that Tsc22d3 was involved in leukemia. Functional enrichment analysis showed that the Tsc22d3 gene has many biological functions, including the regulation of many genes, kinases, miRNAs, signaling pathways, and immune infiltration.Therefore, this study suggests that the Tsc22d3 gene may be a potential therapeutic target for AML. Conclusions: Tsc22d3 gene expression was upregulated in AML, and overexpression was associated with poor OS in AML patients. Therefore, the Tsc22d3 gene may serve as a novel prognostic biomarker and therapeutic target for AML.

Clinical relevance of proteomic profiling in de novo pediatric acute myeloid leukemia: a Children’s Oncology Group study

Pediatric acute myeloid leukemia (AML) remains a fatal disease for at least 30% of patients, stressing the need for improved therapies and better risk stratification. As proteins are the unifying feature of (epi)genetic and environmental alterations, and are often targeted by novel chemotherapeutic agents, we studied the proteomic landscape of pediatric AML. Protein expression and activation levels were measured in 500 bulk leukemic patient samples and 30 control CD34+ samples, using the reverse phase protein arrays with 296 strictly validated antibodies. The multi-step “MetaGalaxy” analysis methodology was applied and identified nine protein expression signatures (PrSIG), based on strong recurrent protein expression patterns. PrSIGs were associated with cytogenetics and mutational state, and with both favorable or unfavorable prognosis. Analysis based on treatment (i.e., ADE vs. ADE plus bortezomib (ADEB)) identified three PrSIGs that did better with ADEB vs. ADE. When PrSIGs were studied in the context of genetic subgroups, PrSIGs were independently prognostic after multivariate analysis, suggesting a potential value for proteomics in combination with current classification systems. Proteins with universally increased (n=7) or decreased (n=17) expression were observed across PrSIGs. Expression of certain proteins significantly differentially expressed from normal could be identified, forming a hypothetical platform for personalized medicine.