Combinatorial genetics reveals the Dock1-Rac2 axis as a potential target for the treatment of NPM1;Cohesin mutated 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.

Cohesin mutations in acute myeloid leukemia

The cohesin complex, encoded by SMC3, SMC1A, RAD21, and STAG2, is a critical regulator of DNA-looping and gene expression. Over a decade has passed since recurrent mutations affecting cohesin subunits were first identified in myeloid malignancies such as Acute Myeloid Leukemia (AML). Since that time there has been tremendous progress in our understanding of chromatin structure and cohesin biology, but critical questions remain because of the multiple critical functions the cohesin complex is responsible for. Recent findings have been particularly noteworthy with the identification of crosstalk between DNA-looping and chromatin domains, a deeper understanding of how cohesin establishes sister chromatid cohesion, a renewed interest in cohesin's role for DNA damage response, and work demonstrating cohesin's importance for Polycomb repression. Despite these exciting findings, the role of cohesin in normal hematopoiesis, and the precise mechanisms by which cohesin mutations promote cancer, remain poorly understood. This review discusses what is known about the role of cohesin in normal hematopoiesis, and how recent findings could shed light on the mechanisms through which cohesin mutations promote leukemic transformation. Important unanswered questions in the field, such as whether cohesin plays a role in HSC heterogeneity, and the mechanisms by which it regulates gene expression at a molecular level, will also be discussed. Particular attention will be given to the potential therapeutic vulnerabilities of leukemic cells with cohesin subunit mutations.

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and drug response. We utilized 13 PCD pathways, including apoptosis, pyroptosis, ferroptosis, autophagy, necroptosis, cuproptosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis to develop predictive models based on 73 machine learning combinations from 10 algorithms. Bulk RNA-sequencing, single-cell RNA-sequencing transcriptomic data, and matched clinicopathological information were obtained from the TCGA-AML, Tyner, and GSE37642-GPL96 cohorts. These datasets were leveraged to construct and validate the models. Additionally, in vitro experiments were conducted to substantiate the bioinformatics findings. The machine learning approach established a 6-gene pan-programmed cell death-related genes index (PPCDI) signature. Validation in two external cohorts showed high PPCDI associated with worse prognosis in AML patients. Incorporating PPCDI with clinical variables, we constructed several robust prognostic nomograms that accurately predicted prognosis of AML patients. Multi-omics analysis integrating bulk and single-cell transcriptomics revealed correlations between PPCDI and immunological features, delineating the immune microenvironment landscape in AML. Patients with high PPCDI exhibited resistance to conventional chemotherapy like doxorubicin but retained sensitivity to dasatinib and methotrexate (FDA-approved drugs for other leukemias), suggesting the potential of PPCDI to guide personalized therapy selection in AML. In summary, we developed a novel PPCDI model through comprehensive analysis of diverse programmed cell death pathways. This PPCDI signature demonstrates great potential in predicting clinical prognosis and drug sensitivity phenotypes in AML patients.

Genetic change investigation in DOCK1 gene in an Iranian family with sign and symptoms of temporomandibular joint disorder (TMD)

OBJECTIVES

Temporomandibular joint disorder (TMD) is a complex condition with pain and dysfunction in the temporomandibular joint and related muscles. Scientific evidence indicates both genetic and environmental factors play a crucial role in TMD. In this study, we aimed to discover the genetic changes in individuals from 4 generations of an Iranian family with signs and symptoms of TMD and malocclusion Class III.

MATERIALS AND METHODS

Whole Exome Sequencing (WES) was performed in 4 patients (IV-8, IV-9, V-4, and V-6) with TMD according to (DC/TMD), along with skeletal Class III malocclusion. Then, PCR sequencing was performed on 23 family members to confirm the WES.

RESULTS

In the present study, WES results analysis detected 6 heterozygous non-synonymous Single Nucleotide Variants (SNVs) in 5 genes, including CRLF3, DNAH17, DOCK1, SEPT9, and VWDE. A heterozygous variant, c.2012T > A (p.F671Y), in Exon 20 of the DOCK1 (NM_001290223.2) gene was identified. Then, this variant was investigated in 19 other members of the same family. PCR-Sequencing results showed that 7/19 had heterozygous TA genotype, all of whom were accompanied by malocclusion and TMD symptoms and 12/19 individuals had homozygous TT genotype, 9 of whom had no temporomandibular joint problems or malocclusion. The remaining 3 showed mild TMD clinical symptoms. The 5 other non-synonymous SNVs of CRLF3, DNAH17, SEPT9, and VWDE were not considered plausible candidates for TMD.

CONCLUSIONS

The present study identified a heterozygous nonsynonymous c.2012T > A (p.F671Y) variant of the DOCK1 gene is significantly associated with skeletal class III malocclusion, TMD, and its severity in affected individuals in the Iranian pedigree.

CLINICAL RELEVANCE

The role of genetic factors in the development of TMD has been described. The present study identified a nonsynonymous variant of the DOCK1 gene as a candidate for TMD and skeletal class III malocclusion in affected individuals in the Iranian pedigree.

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.

Cohesin loss and MLL-AF9 are not synthetic lethal in murine hematopoietic stem and progenitor cells

Objective As cohesin mutations are rarely found in MLL-rearranged acute myeloid leukemias, we investigated the potential synthetic lethality between cohesin mutations and MLL-AF9 using murine hematopoietic stem and progenitor cells. Results Contrary to our hypothesis, a complete loss of Stag2 or haploinsufficiency of Smc3 were well tolerated in MLL-AF9-expressing hematopoietic stem and progenitor cells. Minimal effect of cohesin subunit loss on the in vitro self-renewal of MLL-AF9-expressing cells was observed. Despite the differing mutational landscapes of cohesin-mutated and MLL fusion AMLs, previous studies showed that cohesin and MLL fusion mutations similarly drive abnormal self-renewal through HOXA gene upregulation. The utilization of a similar mechanism suggests that little selective pressure exists for the acquisition of cohesin mutations in AMLs expressing MLL fusions, explaining their lack of co-occurrence. Our results emphasize the importance of using genetic models to test suspected synthetic lethality and suggest that a lack of co-occurrence may instead point to a common mechanism of action between two mutations.

Genetic, Phenotypic, and Clinical Heterogeneity of NPM1-Mutant Acute Myeloid Leukemias

The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. AML with mutated nucleophosmin 1 (NPM1-mut) is the largest of the genetically defined groups, involving about 30% of adult AMLs and is currently recognized as a distinct entity in the actual AML classifications. NPM1-mut AML usually occurs in de novo AML and is associated predominantly with a normal karyotype and relatively favorable prognosis. However, NPM1-mut AMLs are genetically, transcriptionally, and phenotypically heterogeneous. Furthermore, NPM1-mut is a clinically heterogenous group. Recent studies have in part clarified the consistent heterogeneities of these AMLs and have strongly supported the need for an additional stratification aiming to improve the therapeutic response of the different subgroups of NPM1-mut AML patients.