Multi-omics reveals mitochondrial metabolism proteins susceptible for drug discovery in AML

Omics approaches: Role in acute myeloid leukemia biomarker discovery and therapy

Acute myeloid leukemia (AML) is the most common acute leukemia in adults and has the highest fatality rate. Patients aged 65 and above exhibit the poorest prognosis, with a mere 30 % survival rate within one year. One important issue in optimizing outcomes for AML patients is their limited ability to predict responses to specific therapies, response duration, and likelihood of relapse. Despite rigorous therapeutic interventions, a significant proportion of patients experience relapse. Consequently, there is a pressing need to introduce new targets for therapy. Sequencing and biotechnology have come a long way in the last ten years. This has made it easier for many omics technologies, like genomics, transcriptomics, proteomics, and metabolomics, to study molecular mechanisms of AML. An integrative approach is necessary to understand a complex biological process fully and offers an important opportunity to understand the information underlying diseases. In this review, we studied papers published between 2010 and 2024 employing omics approaches encompassing diagnosis, prognosis, and risk stratification of AML. Finally, we discuss prospects and challenges in applying -omics technologies to the discovery of novel biomarkers and therapy targets. Our review may be helpful for omics researchers who want to study AML from different molecular aspects.

Proteomics reveals genetic mechanisms of cold resistance in Hezuo pig liver tissue

Cold stress poses a significant challenge to pig farming in northern China, leading to reduced productivity and, in severe cases, even mortality. However, the mechanisms underlying cold resistance in pigs are not well understood. To explore the genetic mechanism of cold resistance in pigs under low-temperature conditions, the cold-tolerant Hezuo pig was selected as a model. DIA proteomics analysis was performed on liver tissues from Hezuo pigs after 24 h of exposure to low-temperature treatments. The results showed that approximately 149 differential abundance proteins (DAPs) were detected (95 up-regulated and 54 down-regulated). GO analysis showed that these DAPs were mainly associated with lipid metabolism, vesicle fusion, and membrane function. KEGG analysis showed that these DAPs were primarily enriched in lipid metabolism-related pathways such as cholesterol metabolism and vitamin digestion and absorption. Comprehensive analysis identified APOA4, APOA2, SREBF2, ATP23, STX2, USO1, ETFA, RAB11FIP1, ETNPPL, and SGMS1 as potential key proteins involved in cold resistance mechanisms. The mRNA expression of the genes for two key candidate proteins (APOA4 and SREBF2), which are involved in lipid metabolism, was analyzed using qRT-PCR, revealing a significant up-regulation after low-temperature treatment. These findings provide significant insights into the mechanisms of cold resistance in animals and may serve as candidate markers for further studies on cold tolerance. SIGNIFICANCE: Cold resistance is one of the key traits in pigs and involves multiple complex coordinated regulatory mechanisms. However, its genetic mechanisms are not completely understood. In this study, a DIA proteomics approach was used to identify proteins and pathways associated with cold resistance in the liver of low-temperature-treated Hezuo pigs. These findings offer novel candidate proteins and key pathways for investigating the molecular mechanisms of cold resistance in Hezuo pigs, providing a base for further elucidating the mechanisms of cold tolerance in pigs.

Exploring Aerobic Energy Metabolism in Breast Cancer: A Mutational Profile of Glycolysis and Oxidative Phosphorylation

Energy metabolism is a fundamental aspect of the aggressiveness and invasiveness of breast cancer (BC), the neoplasm that most affects women worldwide. Nonetheless, the impact of genetic somatic mutations on glycolysis and oxidative phosphorylation (OXPHOS) genes in BC remains unclear. To fill these gaps, the mutational profiles of 205 screened genes related to glycolysis and OXPHOS in 968 individuals with BC from The Cancer Genome Atlas (TCGA) project were performed. We carried out analyses to characterize the mutational profile of BC, assess the clonality of tumors, identify somatic mutation co-occurrence, and predict the pathogenicity of these alterations. In total, 408 mutations in 132 genes related to the glycolysis and OXPHOS pathways were detected. The PGK1, PC, PCK1, HK1, DONSON, GPD1, NDUFS1, and FOXRED1 genes are also associated with the tumorigenesis process in other types of cancer, as are the genes BRCA1, BRCA2, and HMCN1, which had been previously described as oncogenes in BC, with whom the target genes of this work were associated. Seven mutations were identified and highlighted due to the high pathogenicity, which are present in more than one of our results and are documented in the literature as being correlated with other diseases. These mutations are rs267606829 (FOXRED1), COSV53860306 (HK1), rs201634181 (NDUFS1), rs774052186 (DONSON), rs119103242 (PC), rs1436643226 (PC), and rs104894677 (ETFB). They could be further investigated as potential biomarkers for diagnosis, prognosis, and treatment of BC patients.

DOGMA-seq and multimodal, single-cell analysis in acute myeloid leukemia

Acute myeloid leukemia (AML) is a complex cancer, yet advances in recent years from integrated genomics methods have helped improve diagnosis, treatment, and means of patient stratification. A recent example of a powerful, multimodal method is DOGMA-seq, which can measure chromatin accessibility, gene expression, and cell-surface protein levels from the same individual cell simultaneously. Previous bimodal single-cell techniques, such as CITE-seq (Cellular indexing of transcriptomes and epitopes), have only permitted the transcriptome and cell-surface protein expression measurement. DOGMA-seq, however, builds on this foundation and has implications for examining epigenomic, transcriptomic, and proteomic interactions between various cell types. This technique has the potential to be particularly useful in the study of cancers such as AML. This is because the cellular mechanisms that drive AML are rather heterogeneous and require a more complete understanding of the interplay between the genetic mutations, disruptions in RNA transcription and translation, and surface protein expression that cause these cancers to develop and evolve. This technique will hopefully contribute to a more clear and complete understanding of the growth and progression of complex cancers.

Deciphering genetic and nongenetic factors underlying tumour dormancy: insights from multiomics analysis of two syngeneic MRD models of melanoma and leukemia

BACKGROUND

Tumour dormancy, a resistance mechanism employed by cancer cells, is a significant challenge in cancer treatment, contributing to minimal residual disease (MRD) and potential relapse. Despite its clinical importance, the mechanisms underlying tumour dormancy and MRD remain unclear. In this study, we employed two syngeneic murine models of myeloid leukemia and melanoma to investigate the genetic, epigenetic, transcriptomic and protein signatures associated with tumour dormancy. We used a multiomics approach to elucidate the molecular mechanisms driving MRD and identify potential therapeutic targets.

RESULTS

We conducted an in-depth omics analysis encompassing whole-exome sequencing (WES), copy number variation (CNV) analysis, chromatin immunoprecipitation followed by sequencing (ChIP-seq), transcriptome and proteome investigations. WES analysis revealed a modest overlap of gene mutations between melanoma and leukemia dormancy models, with a significant number of mutated genes found exclusively in dormant cells. These exclusive genetic signatures suggest selective pressure during MRD, potentially conferring resistance to the microenvironment or therapies. CNV, histone marks and transcriptomic gene expression signatures combined with Gene Ontology (GO) enrichment analysis highlighted the potential functional roles of the mutated genes, providing insights into the pathways associated with MRD. In addition, we compared "murine MRD genes" profiles to the corresponding human disease through public datasets and highlighted common features according to disease progression. Proteomic analysis combined with multi-omics genetic investigations, revealed a dysregulated proteins signature in dormant cells with minimal genetic mechanism involvement. Pathway enrichment analysis revealed the metabolic, differentiation and cytoskeletal remodeling processes involved in MRD. Finally, we identified 11 common proteins differentially expressed in dormant cells from both pathologies.

CONCLUSIONS

Our study underscores the complexity of tumour dormancy, implicating both genetic and nongenetic factors. By comparing genomic, transcriptomic, proteomic, and epigenomic datasets, our study provides a comprehensive understanding of the molecular landscape of minimal residual disease. These results provide a robust foundation for forthcoming investigations and offer potential avenues for the advancement of targeted MRD therapies in leukemia and melanoma patients, emphasizing the importance of considering both genetic and nongenetic factors in treatment strategies.

Spontaneous-stimulated Raman co-localization dual-modal analysis approach for efficient identification of tumor cells

The study of highly heterogeneous tumor cells, especially acute myeloid leukemia (AML) cells, usually relies on invasive analytical methods such as morphology, immunology, cytogenetics, and molecular biology classification, which are complex and time-consuming to perform. Mortality is high if patients are not diagnosed in a timely manner, so rapid label-free analysis of gene expression and metabolites within single-cell substructures is extremely important for clinical diagnosis and treatment. As a label-free and non-destructive vibrational detection technique, spontaneous Raman scattering provides molecular information across the full spectrum of the cell but lacks rapid imaging localization capabilities. In contrast, stimulated Raman scattering (SRS) provides a high-speed, high-resolution imaging view that can offer real-time subcellular localization assistance for spontaneous Raman spectroscopic detection. In this paper, we combined multi-color SRS microscopy with spontaneous Raman to develop a co-localized Raman imaging and spectral detection system (CRIS) for high-speed chemical imaging and quantitative spectral analysis of subcellular structures. Combined with multivariate statistical analysis methods, CRIS efficiently differentiated AML from normal leukocytes with an accuracy of 98.1 % and revealed the differences in the composition of nuclei and cytoplasm of AML relative to normal leukocytes. Compared to conventional Raman spectroscopy blind sampling without imaging localization, CRIS increased the efficiency of single-cell detection by at least three times. In addition, using the same approach for further identification of AML subtypes M2 and M3, we demonstrated that intracytoplasmic differential expression of proteins is a marker for their rapid and accurate classifying. CRIS analysis methods are expected to pave the way for clinical translation of rapid tumor cell identification.

The Art of Finding the Right Drug Target: Emerging Methods and Strategies

Drug targets are specific molecules in biological tissues and body fluids that interact with drugs. Drug target discovery is a key component of drug discovery and is essential for the development of new drugs in areas such as cancer therapy and precision medicine. Traditional in vitro or in vivo target discovery methods are time-consuming and labor-intensive, limiting the pace of drug discovery. With the development of modern discovery methods, the discovery and application of various emerging technologies have greatly improved the efficiency of drug discovery, shortened the cycle time, and reduced the cost. This review provides a comprehensive overview of various emerging drug target discovery strategies, including computer-assisted approaches, drug affinity response target stability, multiomics analysis, gene editing, and nonsense-mediated mRNA degradation, and discusses the effectiveness and limitations of the various approaches, as well as their application in real cases. Through the review of the aforementioned contents, a general overview of the development of novel drug targets and disease treatment strategies will be provided, and a theoretical basis will be provided for those who are engaged in pharmaceutical science research. SIGNIFICANCE STATEMENT: Target-based drug discovery has been the main approach to drug discovery in the pharmaceutical industry for the past three decades. Traditional drug target discovery methods based on in vivo or in vitro validation are time-consuming and costly, greatly limiting the development of new drugs. Therefore, the development and selection of new methods in the drug target discovery process is crucial.

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.

High Mitochondrial Protein Expression as a Potential Predictor of Relapse Risk in Acute Myeloid Leukemia Patients with the Monocytic FAB Subtypes M4 and M5

AML is a highly aggressive and heterogeneous form of hematological cancer. Proteomics-based stratification of patients into more refined subgroups may contribute to a more precise characterization of the patient-derived AML cells. Here, we reanalyzed liquid chromatography-tandem mass spectrometry (LC-MS/MS) generated proteomic and phosphoproteomic data from 26 FAB-M4/M5 patients. The patients achieved complete hematological remission after induction therapy. Twelve of them later developed chemoresistant relapse (RELAPSE), and 14 patients were relapse-free (REL_FREE) long-term survivors. We considered not only the RELAPSE and REL_FREE characteristics but also integrated the French-American-British (FAB) classification, along with considering the presence of nucleophosmin 1 (NPM1) mutation and cytogenetically normal AML. We found a significant number of differentially enriched proteins (911) and phosphoproteins (257) between the various FAB subtypes in RELAPSE patients. Patients with the myeloblastic M1/M2 subtype showed higher levels of RNA processing-related routes and lower levels of signaling related to terms like translation and degranulation when compared with the M4/M5 subtype. Moreover, we found that a high abundance of proteins associated with mitochondrial translation and oxidative phosphorylation, particularly observed in the RELAPSE M4/M5 NPM1 mutated subgroup, distinguishes relapsing from non-relapsing AML patient cells with the FAB subtype M4/M5. Thus, the discovery of subtype-specific biomarkers through proteomic profiling may complement the existing classification system for AML and potentially aid in selecting personalized treatment strategies for individual patients.

FBXO21 mediated degradation of p85α regulates proliferation and survival of acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by clonal expansion of myeloid blasts in the bone marrow (BM). Despite advances in therapy, the prognosis for AML patients remains poor, and there is a need to identify novel molecular pathways regulating tumor cell survival and proliferation. F-box ubiquitin E3 ligase, FBXO21, has low expression in AML, but expression correlates with survival in AML patients and patients with higher expression have poorer outcomes. Silencing FBXO21 in human-derived AML cell lines and primary patient samples leads to differentiation, inhibition of tumor progression, and sensitization to chemotherapy agents. Additionally, knockdown of FBXO21 leads to up-regulation of cytokine signaling pathways. Through a mass spectrometry-based proteomic analysis of FBXO21 in AML, we identified that FBXO21 ubiquitylates p85α, a regulatory subunit of the phosphoinositide 3-kinase (PI3K) pathway, for degradation resulting in decreased PI3K signaling, dimerization of free p85α and ERK activation. These findings reveal the ubiquitin E3 ligase, FBXO21, plays a critical role in regulating AML pathogenesis, specifically through alterations in PI3K via regulation of p85α protein stability.

Targeting chemoresistance and mitochondria-dependent metabolic reprogramming in acute myeloid leukemia

Chemoresistance often complicates the management of cancer, as noted in the instance of acute myeloid leukemia (AML). Mitochondrial function is considered important for the viability of AML blasts and appears to also modulate chemoresistance. As mitochondrial metabolism is aberrant in AML, any distinct pathways could be directly targeted to impact both cell viability and chemoresistance. Therefore, identifying and targeting those precise rogue elements of mitochondrial metabolism could be a valid therapeutic strategy in leukemia. Here, we review the evidence for abnormalities in mitochondria metabolic processes in AML cells, that likely impact chemoresistance. We further address several therapeutic approaches targeting isocitrate dehydrogenase 2 (IDH2), CD39, nicotinamide phosphoribosyl transferase (NAMPT), electron transport chain (ETC) complex in AML and also consider the roles of mesenchymal stromal cells. We propose the term "mitotherapy" to collectively refer to such regimens that attempt to override mitochondria-mediated metabolic reprogramming, as used by cancer cells. Mounting evidence suggests that mitotherapy could provide a complementary strategy to overcome chemoresistance in liquid cancers, as well as in solid tumors.

Proteomic Characterization of Acute Myeloid Leukemia for Precision Medicine

Acute myeloid leukemia (AML) is a highly heterogeneous cancer of the hematopoietic system with no cure for most patients. In addition to chemotherapy, treatment options for AML include recently approved therapies that target proteins with roles in AML pathobiology, such as FLT3, BLC2, and IDH1/2. However, due to disease complexity, these therapies produce very diverse responses, and survival rates are still low. Thus, despite considerable advances, there remains a need for therapies that target different aspects of leukemic biology and for associated biomarkers that define patient populations likely to respond to each available therapy. To meet this need, drugs that target different AML vulnerabilities are currently in advanced stages of clinical development. Here, we review proteomics and phosphoproteomics studies that aimed to provide insights into AML biology and clinical disease heterogeneity not attainable with genomic approaches. To place the discussion in context, we first provide an overview of genetic and clinical aspects of the disease, followed by a summary of proteins targeted by compounds that have been approved or are under clinical trials for AML treatment and, if available, the biomarkers that predict responses. We then discuss proteomics and phosphoproteomics studies that provided insights into AML pathogenesis, from which potential biomarkers and drug targets were identified, and studies that aimed to rationalize the use of synergistic drug combinations. When considered as a whole, the evidence summarized here suggests that proteomics and phosphoproteomics approaches can play a crucial role in the development and implementation of precision medicine for AML patients.

Ubiquitin E3 ligase FBXO21 regulates cytokine-mediated signaling pathways, but is dispensable for steady-state hematopoiesis

Hematopoietic cell fate decisions such as self-renewal and differentiation are highly regulated through multiple molecular pathways. One pathway, the ubiquitin proteasome system (UPS), controls protein levels by tagging them with polyubiquitin chains and promoting their degradation through the proteasome. Ubiquitin E3 ligases serve as the substrate-recognition component of the UPS. By investigating the FBOX family of E3 ligases, we discovered that Fbxo21 was highly expressed in the hematopoietic stem and progenitor cell (HSPC) population, and exhibited low to no expression in mature myeloid populations. To determine the role of FBXO21 on HSPC maintenance, self-renewal, and differentiation, we generated shRNAs against FBXO21 and a hematopoiesis-specific Fbxo21 conditional knockout (cKO) mouse model. We found that silencing FBXO21 in HSPCs led to a loss in colony formation and an increase in cell differentiation in vitro. Additionally, stressing the HSPC populations in our Fbxo21 cKO mouse with 5-fluorouracil injections resulted in a decrease in survival, despite these populations exhibiting minimal alterations during steady-state hematopoiesis. Although FBXO21 has previously been proposed to regulate cytokine signaling via ASK and p38, our results indicate that depletion of FBXO21 led to altered ERK signaling in vitro. Together, these findings suggest ubiquitin E3 ligase FBXO21 regulates HSPCs through cytokine-mediated pathways.

Machine Learning Assistants Construct Oxidative Stress-Related Gene Signature and Discover Potential Therapy Targets for Acute Myeloid Leukemia

Background

Oxidative stress (OS) is associated with the development of acute myeloid leukemia (AML). However, there is lack of relevant research to confirm that OS-related genes can guide patients in risk stratification and predict their survival probability.

Method

First, we Data from three public databases, respectively. Then, we use batch univariate Cox regression and machine learning to select important characteristic genes; next, we build the model and use receiver operating characteristic curve (ROC) to evaluate the accuracy. Moreover, GSEAs were performed to discover the molecular mechanism and conduct nomogram visualization. In addition, the relative importance value was used to identify the hub gene, and GSE9476 was to validate hub gene difference expression. Finally, we use symptom mapping to predict the candidate herbs, targeting the hub gene, and put these candidate herbs into Traditional Chinese Medicine Systems Pharmacology (TCMSP) to identify the main small molecular ingredients and then docking hub proteins with this small molecular.

Results

A total of 313 candidate oxidative stress-related genes could affect patients' outcomes and machine learning to select six potential genes to construct a gene signature model to predict the overall survival (OS) of AML patients. Patients in a high group will obtain a short survival time when compared with the low-risk group (HR = 3.97, 95% CI: 2.48-6.36; p < 0.001). ROC results demonstrate the model has better prediction efficiency with AUC 0.873. GSEA suggests that this gene is enriched in several important signaling pathways. Nomogram is constructed and is robust. PLA2G4A is a hub gene of signature and associated with prognosis, and Nobiletin could target PLA2G4A for therapy AML.

Conclusion

We use two different machine learning methods to build six oxidative stress-related gene signatures that could assist clinical decisions and identify PLA2G4A as a potential biomarker for AML. Nobiletin, targeting PLA2G4, may provide a third pathway for therapy AML.