Transcriptional signatures of the BCL2 family for individualized acute myeloid leukaemia treatment

Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells

OBJECTIVE

Gastric cancer (GC) is one of the most common malignancies seen in clinic and requires novel treatment options. Morin is a natural flavonoid extracted from the flower stalk of a highly valuable medicinal plant Prunella vulgaris L., which exhibits an anti-cancer effect in multiple types of tumors. However, the therapeutic effect and underlying mechanism of morin in treating GC remains elusive. The study aims to explore the therapeutic effect and underlying molecular mechanisms of morin in GC.

METHODS

For in vitro experiments, the proliferation inhibition of morin was measured by cell counting kit-8 assay and colony formation assay in human GC cell line MKN45, human gastric adenocarcinoma cell line AGS, and human gastric epithelial cell line GES-1; for apoptosis analysis, microscopic photography, Western blotting, ubiquitination analysis, quantitative polymerase chain reaction analysis, flow cytometry, and RNA interference technology were employed. For in vivo studies, immunohistochemistry, biomedical analysis, and Western blotting were used to assess the efficacy and safety of morin in a xenograft mouse model of GC.

RESULTS

Morin significantly inhibited the proliferation of GC cells MKN45 and AGS in a dose- and time-dependent manner, but did not inhibit human gastric epithelial cells GES-1. Only the caspase inhibitor Z-VAD-FMK was able to significantly reverse the inhibition of proliferation by morin in both GC cells, suggesting that apoptosis was the main type of cell death during the treatment. Morin induced intrinsic apoptosis in a dose-dependent manner in GC cells, which mainly relied on B cell leukemia/lymphoma 2 (BCL-2) associated agonist of cell death (BAD) but not phorbol-12-myristate-13-acetate-induced protein 1. The upregulation of BAD by morin was due to blocking the ubiquitination degradation of BAD, rather than the transcription regulation and the phosphorylation of BAD. Furthermore, the combination of morin and BCL-2 inhibitor navitoclax (also known as ABT-737) produced a synergistic inhibitory effect in GC cells through amplifying apoptotic signals. In addition, morin treatment significantly suppressed the growth of GC in vivo by upregulating BAD and the subsequent activation of its downstream apoptosis pathway.

CONCLUSION

Morin suppressed GC by inducing apoptosis, which was mainly due to blocking the ubiquitination-based degradation of the pro-apoptotic protein BAD. The combination of morin and the BCL-2 inhibitor ABT-737 synergistically amplified apoptotic signals in GC cells, which may overcome the drug resistance of the BCL-2 inhibitor. These findings indicated that morin was a potent and promising agent for GC treatment. Please cite this article as: Wang Y, Sun XY, Ma FQ, Ren MM, Zhao RH, Qin MM, Zhu XH, Xu Y, Cao ND, Chen YY, Dong TG, Pan YF, Zhao AG. Morin inhibits ubiquitination degradation of BCL-2 associated agonist of cell death and synergizes with BCL-2 inhibitor in gastric cancer cells. J Integr Med. 2025; Epub ahead of print.

Targeting mitochondrial RNAs enhances the efficacy of the DNA-demethylating agents

Hypomethylating agents (HMAs) such as azacytidine and decitabine are FDA-approved chemotherapy drugs for hematologic malignancy. By inhibiting DNA methyltransferases, HMAs reactivate tumor suppressor genes (TSGs) and endogenous double-stranded RNAs (dsRNAs) that limit tumor growth and trigger apoptosis via viral mimicry. Yet, HMAs show limited effects in many solid tumors despite the strong induction of TSGs and dsRNAs. Here we show that targeting mitochondrial RNAs (mtRNAs) can enhance the HMA-mediated cell death in lung adenocarcinoma cells. We find that HMA treatment accompanies increased mtRNA levels and subsequent enhancement of metabolic activity, resulting in higher ATP production. Compromising the mitochondrial function by downregulating mature mtRNA expression increased cell death by HMAs. We further perform a CRISPR screening on mtRNA processing factors and find that mtRNA polymerase (POLRMT) and ElaC Ribonuclease Z 2 (ELAC2) depleted cells show increased sensitivity to HMAs by suppressing decitabine-triggered enhancement of ATP production. Moreover, we show that a small molecular inhibitor of POLRMT compromises the metabolic activity and synergistically enhances the cytotoxicity of HMAs. Our study unveils the insensitivity to HMAs through the elevation of mtRNAs and suggests mtRNA regulatory factors as potential synergistic targets to improve the therapeutic benefit of HMAs.

Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia

Acute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.

Predicting the risk of primary Sjögren's syndrome with key N7-methylguanosine-related genes: A novel XGBoost model

Objectives

N7-methylguanosine (m7G) plays a crucial role in mRNA metabolism and other biological processes. However, its regulators' function in Primary Sjögren's Syndrome (PSS) remains enigmatic.

Methods

We screened five key m7G-related genes across multiple datasets, leveraging statistical and machine learning computations. Based on these genes, we developed a prediction model employing the extreme gradient boosting decision tree (XGBoost) method to assess PSS risk. Immune infiltration in PSS samples was analyzed using the ssGSEA method, revealing the immune landscape of PSS patients.

Results

The XGBoost model exhibited high accuracy, AUC, sensitivity, and specificity in both training, test sets and extra-test set. The decision curve confirmed its clinical utility. Our findings suggest that m7G methylation might contribute to PSS pathogenesis through immune modulation.

Conclusions

m7G regulators play an important role in the development of PSS. Our study of m7G-realted genes may inform future immunotherapy strategies for PSS.

Single-cell transcriptomics dissects the transcriptome alterations of hematopoietic stem cells in myelodysplastic neoplasms

BACKGROUND

Myelodysplastic neoplasms (MDS) are myeloid neoplasms characterized by disordered differentiation of hematopoietic stem cells and a predisposition to acute myeloid leukemia (AML). The underline pathogenesis remains unclear.

METHODS

In this study, the trajectory of differentiation and mechanisms of leukemic transformation were explored through bioinformatics analysis of single-cell RNA-Seq data from hematopoietic stem and progenitor cells (HSPCs) in MDS patients.

RESULTS

Among the HSPC clusters, the proportion of common myeloid progenitor (CMP) was the main cell cluster in the patients with excess blasts (EB)/ secondary AML. Cell cycle analysis indicated the CMP of MDS patients were in an active proliferative state. The genes involved in the cell proliferation, such as MAML3 and PLCB1, were up-regulated in MDS CMP. Further validation analysis indicated that the expression levels of MAML3 and PLCB1 in patients with MDS-EB were significantly higher than those without EB. Patients with high expression of PLCB1 had a higher risk of transformation to AML. PLCB1 inhibitor can suppress proliferation, induce cell cycle arrest, and activate apoptosis of leukemic cells in vitro.

CONCLUSION

This study revealed the transcriptomic change of HSPCs in MDS patients along the pseudotime and indicated that PLCB1 plays a key role in the transformation of MDS into leukemia.

Identification of disulfidptosis-related genes and immune infiltration in lower-grade glioma

Lower-grade glioma (LGG), a prevalent malignant tumor in the central nervous system, requires accurate prediction and treatment to prevent aggressive progression. We aimed to explore the role of disulfidptosis-related genes (DRGs) in LGG, a recently discovered form of programmed cell death characterized by abnormal disulfide accumulation. Leveraging public databases, we analyzed 532 LGG tumor tissues (The Cancer Genome Atlas), 1,157 normal samples (Genotype-Tissue Expression), and 21 LGG tumor samples with 8 paired normal samples (GSE16011). Our research uncovered intricate relationships between DRGs and crucial aspects of LGG, including gene expression, immune response, mutation, drug sensitivity, and functional enrichment. Notably, we identified significant heterogeneity among disulfidptosis sub-clusters and elucidated specific differential gene expression in LGG, with myeloid cell leukemia-1 (MCL1) as a key candidate. Machine learning techniques validated the relevance of MCL1, considering its expression patterns, prognostic value, diagnostic potential, and impact on immune infiltration. Our study offers opportunities and challenges to unravel potential mechanisms underlying LGG prognosis, paving the way for personalized cancer care and innovative immunotherapeutic strategies. By shedding light on DRGs, particularly MCL1, we enhance understanding and management of LGG.

Comprehensive analysis of clinical prognostic features and tumor microenvironment landscape of CD11b+CD64+ patients with acute myeloid leukemia

BACKGROUND

Immunophenotyping surface molecules detected in the clinic are mainly applied in diagnostic confirmation and subtyping. However, the immunomodulatory molecules CD11b and CD64, are highly associated with leukemogenesis. Hence, the prognostic value of them and their potential biological functions merit further investigation.

METHODS

Flow cytometry was operated to detect immunophenotypic molecules from AML bone marrow samples. Multivariate cox regression, Kaplan-Meier analyses, and nomogram were conducted to predict survival. Transcriptomic data, lymphocyte subsets, and immunohistochemical staining were incorporated to identify potential biological functions of prognostic immunophenotype in acute myeloid leukemia (AML).

RESULTS

We classified 315 newly diagnosed AML patients of our center based on the expression of CD11b and CD64. The CD11b+CD64+ populations were identified as independent risk factors for overall survival and event-free survival of AML, exhibiting specific clinicopathological features. The predictive models based on CD11b+CD64+ showed high classification performance. In addition, the CD11b+CD64+ subset, characterized by high inhibitory immune checkpoints, M2-macrophage infiltration, low anti-tumor effector cells infiltration, as well as abnormal somatic mutation landscape, presented a distinctive tumor microenvironmental landscape. The CD11b+CD64+ population showd a higher expression of BCL2, and the drug sensitivity indicated that they presented a lower half-maximal inhibitory concentration value for BCL2 inhibitor, and could benefit more from the above medicine.

CONCLUSIONS

This work might be of benefit to enhanced understanding of CD11b+CD64+ in the prognosis and leukemogenesis, and yielded novel biomarkers to guide immunotherapy and targeted therapy for AML.