RESUMEN
Acute myeloid leukemia (AML) is a heterogeneous disease characterized by genomic aberrations in oncogenes, cytogenetic abnormalities, and an aberrant epigenetic landscape. Nearly 50% of AML cases will relapse with current treatment. A major source of therapy resistance is the interaction of mesenchymal stroma with leukemic cells resulting in therapeutic protection. We aimed to determine pro-survival/anti-apoptotic protein networks involved in the stroma protection of leukemic cells. Proteomic profiling of cultured primary AML (n = 14) with Hs5 stroma cell line uncovered an up-regulation of energy-favorable metabolic proteins. Next, we modulated stroma-induced drug resistance with an epigenetic drug library, resulting in reduced apoptosis with histone deacetylase inhibitor (HDACi) treatment versus other epigenetic modifying compounds. Quantitative phosphoproteomic probing of this effect further revealed a metabolic-enriched phosphoproteome including significant up-regulation of acetyl-coenzyme A synthetase (ACSS2, S30) in leukemia-stroma HDACi treated cocultures compared with untreated monocultures. Validating these findings, we show ACSS2 substrate, acetate, promotes leukemic proliferation, ACSS2 knockout in leukemia cells inhibits leukemic proliferation and ACSS2 knockout in the stroma impairs leukemic metabolic fitness. Finally, we identify ACSS1/ACSS2-high expression AML subtype correlating with poor overall survival. Collectively, this study uncovers the leukemia-stroma phosphoproteome emphasizing a role for ACSS2 in mediating AML growth and drug resistance.
RESUMEN
Acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis. We report a comprehensive proteogenomic analysis of bone marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none is exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is captured only in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival on treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired toward stronger complex I-dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.
Asunto(s)
Leucemia Mieloide Aguda , Proteogenómica , Humanos , Leucemia Mieloide Aguda/tratamiento farmacológico , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/patología , ProteómicaRESUMEN
Protein interactions are involved in all cellular processes. Their efficient and reliable characterization is therefore essential for understanding biological mechanisms. In this study, we show that combining bacterial artificial chromosome (BAC) TransgeneOmics with quantitative interaction proteomics, which we call quantitative BAC-green fluorescent protein interactomics (QUBIC), allows specific and highly sensitive detection of interactions using rapid, generic, and quantitative procedures with minimal material. We applied this approach to identify known and novel components of well-studied complexes such as the anaphase-promoting complex. Furthermore, we demonstrate second generation interaction proteomics by incorporating directed mutational transgene modification and drug perturbation into QUBIC. These methods identified domain/isoform-specific interactors of pericentrin- and phosphorylation-specific interactors of TACC3, which are necessary for its recruitment to mitotic spindles. The scalability, simplicity, cost effectiveness, and sensitivity of this method provide a basis for its general use in small-scale experiments and in mapping the human protein interactome.