RESUMO
Acute myeloid leukemia (AML) is a complex hematologic malignancy with high morbidity and mortality. Nucleophosmin 1 (NPM1) mutations occur in approximately 30% of AML cases, and NPM1-mutated AML is classified as a distinct entity. NPM1-mutated AML patients without additional genetic abnormalities have a favorable prognosis. Despite this, 30-50% of them experience relapse. This study aimed to investigate the potential of total RNAseq in improving the characterization of NPM1-mutated AML patients. We explored genetic variations independently of myeloid stratification, revealing a complex molecular scenario. We showed that total RNAseq enables the uncovering of different genetic alterations and clonal subtypes, allowing for a comprehensive evaluation of the real expression of exome transcripts in leukemic clones and the identification of aberrant fusion transcripts. This characterization may enhance understanding and guide improved treatment strategies for NPM1mut AML patients, contributing to better outcomes. Our findings underscore the complexity of NPM1-mutated AML, supporting the incorporation of advanced technologies for precise risk stratification and personalized therapeutic strategies. The study provides a foundation for future investigations into the clinical implications of identified genetic variations and highlights the importance of evolving diagnostic approaches in leukemia management.
Assuntos
Neoplasias Hematológicas , Leucemia Mieloide Aguda , Humanos , Células Clonais , Exoma , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/genética , Proteínas Nucleares/genéticaRESUMO
Ewing sarcoma (EWS) is an aggressive pediatric bone tumor characterized by unmet clinical needs and an incompletely understood epigenetic heterogeneity. Here, we considered CD99, a major surface molecule hallmark of EWS malignancy. Fluctuations in CD99 expression strongly impair cell dissemination, differentiation, and death. CD99 is also loaded within extracellular vesicles (EVs), and the delivery of CD99-positive or CD99-negative EVs dynamically exerts oncogenic or oncosuppressive functions to recipient cells, respectively. We undertook mass spectrometry and functional annotation analysis to investigate the consequences of CD99 silencing on the proteomic landscape of EWS cells and related EVs. Our data demonstrate that (i) the decrease in CD99 leads to major changes in the proteomic profile of EWS cells and EVs; (ii) intracellular and extracellular compartments display two distinct signatures of differentially expressed proteins; (iii) proteomic changes converge to the modulation of cell migration and immune-modulation biological processes; and (iv) CD99-silenced cells and related EVs are characterized by a migration-suppressive, pro-immunostimulatory proteomic profile. Overall, our data provide a novel source of CD99-associated protein biomarkers to be considered for further validation as mediators of EWS malignancy and as EWS disease liquid biopsy markers.
Assuntos
Antígeno 12E7 , Neoplasias Ósseas , Vesículas Extracelulares , Sarcoma de Ewing , Criança , Humanos , Antígeno 12E7/metabolismo , Neoplasias Ósseas/metabolismo , Linhagem Celular Tumoral , Movimento Celular/genética , Vesículas Extracelulares/metabolismo , Regulação Neoplásica da Expressão Gênica , Proteínas de Fusão Oncogênica/genética , Proteômica , Sarcoma de Ewing/patologiaRESUMO
AKR1C3 is an upregulated enzyme in prostate and other cancers; in addition to regulating hormone synthesis, this enzyme is thought to play a role in the aggressiveness of tumors and in the defense against drugs. We here used an unbiased method to discover new potent AKR1C3 inhibitors: through an AI-based virtual drug screen, compound 4 was identified as a potent and selective enzymatic inhibitor able to translate this activity into a pronounced antiproliferative effect in the 22RV1 prostate cancer cell model. As other known AKR1C3 inhibitors, compound 4 determined a significantly increased activity of abiraterone, a drug approved for advanced prostate cancer. Compound 4 also showed a synergic effect with doxorubicin in osteosarcoma cell lines; specifically, the effect is correlated with AKR1C3 expression. In this research work, therefore, the use of AI allowed the identification of a new structure as an AKR1C3 inhibitor and its potential to enhance the effect of chemotherapeutics.