Proteomic and genomic integration identifies kinase and differentiation determinants of kinase inhibitor sensitivity in leukemia cells

Genetic Profiling of Acute and Chronic Leukemia via Next-Generation Sequencing: Current Insights and Future Perspectives

Leukemia is a heterogeneous group of hematologic malignancies characterized by distinct genetic and molecular abnormalities. Advancements in genomic technologies have significantly transformed the diagnosis, prognosis, and treatment strategies for leukemia. Among these, next-generation sequencing (NGS) has emerged as a powerful tool, enabling high-resolution genomic profiling that surpasses conventional diagnostic approaches. By providing comprehensive insights into genetic mutations, clonal evolution, and resistance mechanisms, NGS has revolutionized precision medicine in leukemia management. Despite its transformative potential, the clinical integration of NGS presents challenges, including data interpretation complexities, standardization issues, and cost considerations. However, continuous advancements in sequencing platforms and bioinformatics pipelines are enhancing the reliability and accessibility of NGS in routine clinical practice. The expanding role of NGS in leukemia is paving the way for improved risk stratification, targeted therapies, and real-time disease monitoring, ultimately leading to better patient outcomes. This review highlights the impact of NGS on leukemia research and clinical applications, discussing its advantages over traditional diagnostic techniques, key sequencing approaches, and emerging challenges. As precision oncology continues to evolve, NGS is expected to play an increasingly central role in the diagnosis and management of leukemia, driving innovations in personalized medicine and therapeutic interventions.

Phosphoproteomics identifies determinants of PAK inhibitor sensitivity in leukaemia cells

BACKGROUND

The P21 activated kinases (PAK) are frequently dysregulated in cancer and have central roles in oncogenic signalling, prompting the development of PAK inhibitors (PAKi) as anticancer agents. However, such compounds have not reached clinical use because, at least partially, there is a limited mechanistic understanding of their mode of action. Here, we aimed to characterize functional and molecular responses to PAKi (PF-3758309, FRAX-486 and IPA-3) in multiple acute myeloid leukaemia (AML) models to gain insights on the biochemical pathways affected by these inhibitors in this disease and identify determinants of response in patient samples.

METHODS

We mined phosphoproteomic datasets of primary AML, and used proteomics and phosphoproteomics to profile PAKi impact in immortalized (P31/Fuj and MV4-11), and primary AML cells from 8 AML patients. These omics datasets were integrated with gene dependency data to identify which proteins targeted by PAKi are necessary for the proliferation of AML. We studied the effect PAKi on cell cycle progression, proliferation, differentiation and apoptosis. Finally, we used phosphoproteomics data as input for machine learning models that predicted ex vivo response in two independent datasets of primary AML cells (with 36 and 50 cases, respectively) to PF-3758309 and identify markers of response.

RESULTS

We found that PAK1 activation- measured from phosphoproteomics data- was predictive of poor prognosis in primary AML cases. PF-3758309 was the most effective PAKi in reducing proliferation and inducing apoptosis in AML cell lines. In cell lines and primary cells, PF-3758309 inhibited PAK, AMPK and PKCA activities, reduced c-MYC transcriptional activity and the expression of ribosomal proteins, and targeted the FLT3 pathway in FLT3-ITD mutated cells. In primary cells, PF-3758309 reduced STAT5 phosphorylation at Tyr699. Functionally, PF-3758309 reduced cell-growth, induced apoptosis, blocked cell cycle progression and promoted differentiation in a model-dependent manner. ML modelling accurately classified primary AML samples as sensitive or resistant to PF-3758309 ex vivo treatment, and highlighted PHF2 phosphorylation at Ser705 as a robust response biomarker.

CONCLUSIONS

In summary, our data define the proteomic, molecular and functional responses of primary and immortalised AML cells to PF-3758309 and suggest a route to personalise AML treatments based on PAK inhibitors.

Maternal immune activation imprints translational dysregulation and differential MAP2 phosphorylation in descendant neural stem cells

Alterations induced by maternal immune activation (MIA) during gestation impact the subsequent neurodevelopment of progeny, a process that in humans, has been linked to the development of several neuropsychiatric conditions. To undertake a comprehensive examination of the molecular mechanisms governing MIA, we have devised an in vitro model based on neural stem cells (NSCs) sourced from fetuses carried by animals subjected to Poly I:C treatment. These neural progenitors demonstrate proliferative capacity and can be effectively differentiated into both neurons and glial cells. Transcriptomic, proteomic, and phosphoproteomic analyses conducted on these cellular models, in conjunction with counterparts from control treatments, revealed discernible shifts in the expression levels of a specific subset of proteins implicated in neuronal function. Furthermore, the phosphoproteomic data highlighted a discernible discrepancy in the basal phosphorylation of proteins between differentiated cells from both experimental groups, particularly within proteins associated with cytoskeletal architecture and synaptic functionality, notably those belonging to the MAP family. Observed alterations in MAP phosphorylation were found to potentially have functional consequences as they correlate with changes in neuronal plasticity and the establishment of neuronal synapses. Our data agrees with previous published observations and further underscore the importance of MAP2 phosphorylation state on its function and the impact that this protein has in neuronal structure and function.

Stearoyl-CoA desaturase inhibition is toxic to acute myeloid leukemia displaying high levels of the de novo fatty acid biosynthesis and desaturation

Identification of specific and therapeutically actionable vulnerabilities, ideally present across multiple mutational backgrounds, is needed to improve acute myeloid leukemia (AML) patients' outcomes. We identify stearoyl-CoA desaturase (SCD), the key enzyme in fatty acid (FA) desaturation, as prognostic of patients' outcomes and, using the clinical-grade inhibitor SSI-4, show that SCD inhibition (SCDi) is a therapeutic vulnerability across multiple AML models in vitro and in vivo. Multiomic analysis demonstrates that SCDi causes lipotoxicity, which induces AML cell death via pleiotropic effects. Sensitivity to SCDi correlates with AML dependency on FA desaturation regardless of mutational profile and is modulated by FA biosynthesis activity. Finally, we show that lipotoxicity increases chemotherapy-induced DNA damage and standard chemotherapy further sensitizes AML cells to SCDi. Our work supports developing FA desaturase inhibitors in AML while stressing the importance of identifying predictive biomarkers of response and biologically validated combination therapies to realize their full therapeutic potential.

Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia

BACKGROUND

Acute myeloid leukaemia (AML) is a bone marrow malignancy with poor prognosis. One of several treatments for AML is midostaurin combined with intensive chemotherapy (MIC), currently approved for FLT3 mutation-positive (FLT3-MP) AML. However, many patients carrying FLT3 mutations are refractory or experience an early relapse following MIC treatment, and might benefit more from receiving a different treatment. Development of a stratification method that outperforms FLT3 mutational status in predicting MIC response would thus benefit a large number of patients.

METHODS

We employed mass spectrometry phosphoproteomics to analyse 71 diagnosis samples of 47 patients with FLT3-MP AML who subsequently received MIC. We then used machine learning to identify biomarkers of response to MIC, and validated the resulting predictive model in two independent validation cohorts (n = 20).

FINDINGS

We identified three distinct phosphoproteomic AML subtypes amongst long-term survivors. The subtypes showed similar duration of MIC response, but different modulation of AML-implicated pathways, and exhibited distinct, highly-predictive biomarkers of MIC response. Using these biomarkers, we built a phosphoproteomics-based predictive model of MIC response, which we called MPhos. When applied to two retrospective real-world patient test cohorts (n = 20), MPhos predicted MIC response with 83% sensitivity and 100% specificity (log-rank p < 7∗10-5, HR = 0.005 [95% CI: 0-0.31]).

INTERPRETATION

In validation, MPhos outperformed the currently-used FLT3-based stratification method. Our findings have the potential to transform clinical decision-making, and highlight the important role that phosphoproteomics is destined to play in precision oncology.

FUNDING

This work was funded by Innovate UK grants (application numbers: 22217 and 10054602) and by Kinomica Ltd.

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.

Maternal Immune Activation imprints translational dysregulation and differential MAP2 phosphorylation in descendant neural stem cells

Alterations induced by maternal immune activation (MIA) during gestation impact the subsequent neurodevelopment of progeny, a process that in humans, has been linked to the development of several neuropsychiatric conditions. To undertake a comprehensive examination of the molecular mechanisms governing MIA, we have devised an in vitro model based on neural stem cells (NSCs) sourced from fetuses carried by animals subjected to Poly I:C treatment. These neural progenitors demonstrate proliferative capacity and can be effectively differentiated into both neurons and glial cells. Transcriptomic, proteomic, and phosphoproteomic analyses conducted on these cellular models, in conjunction with counterparts from control treatments, revealed discernible shifts in the expression levels of a specific subset of proteins implicated in neuronal function. Noteworthy, we found an absence of congruence between these alterations at the transcriptomic level, suggesting that differences in protein translation contribute to the observed dysregulation. Furthermore, the phosphoproteomic data highlighted a discernible discrepancy in the basal phosphorylation of proteins between differentiated cells from both experimental groups, particularly within proteins associated with cytoskeletal architecture and synaptic functionality, notably those belonging to the MAP family. Observed alterations in MAP phosphorylation were found to potentially have functional consequences as they correlate with changes in neuronal plasticity and the establishment of neuronal synapses. Our data agrees with previous published observations and further underscore the importance of MAP2 phosphorylation state on its function and the impact that this protein has in neuronal structure and function.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

Acute myeloid leukemia is a poor-prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and fail to consistently predict therapeutic response. Here, we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measure the proteome and phosphoproteome of 210 patients and combine them with genomic and transcriptomic measurements to identify four proteogenomic subtypes that complement existing genetic subtypes. We build a predictor to classify samples into subtypes and map them to a "landscape" that identifies specific drug response patterns. We then build a drug response prediction model to identify drugs that target distinct subtypes and validate our findings on cell lines representing various stages of quizartinib resistance. Our results show how multiomics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

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.

Pharmacological approaches to understanding protein kinase signaling networks

Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.

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.

Principles of phosphoproteomics and applications in cancer research

Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.

Proteogenomic analysis of acute myeloid leukemia associates relapsed disease with reprogrammed energy metabolism both in adults and children

Despite improvement of current treatment strategies and novel targeted drugs, relapse and treatment resistance largely determine the outcome for acute myeloid leukemia (AML) patients. To identify the underlying molecular characteristics, numerous studies have been aimed to decipher the genomic- and transcriptomic landscape of AML. Nevertheless, further molecular changes allowing malignant cells to escape treatment remain to be elucidated. Mass spectrometry is a powerful tool enabling detailed insights into proteomic changes that could explain AML relapse and resistance. Here, we investigated AML samples from 47 adult and 22 pediatric patients at serial time-points during disease progression using mass spectrometry-based in-depth proteomics. We show that the proteomic profile at relapse is enriched for mitochondrial ribosomal proteins and subunits of the respiratory chain complex, indicative of reprogrammed energy metabolism from diagnosis to relapse. Further, higher levels of granzymes and lower levels of the anti-inflammatory protein CR1/CD35 suggest an inflammatory signature promoting disease progression. Finally, through a proteogenomic approach, we detected novel peptides, which present a promising repertoire in the search for biomarkers and tumor-specific druggable targets. Altogether, this study highlights the importance of proteomic studies in holistic approaches to improve treatment and survival of AML patients.

Integrative phosphoproteomics defines two biologically distinct groups of KMT2A rearranged acute myeloid leukaemia with different drug response phenotypes

Acute myeloid leukaemia (AML) patients harbouring certain chromosome abnormalities have particularly adverse prognosis. For these patients, targeted therapies have not yet made a significant clinical impact. To understand the molecular landscape of poor prognosis AML we profiled 74 patients from two different centres (in UK and Finland) at the proteomic, phosphoproteomic and drug response phenotypic levels. These data were complemented with transcriptomics analysis for 39 cases. Data integration highlighted a phosphoproteomics signature that define two biologically distinct groups of KMT2A rearranged leukaemia, which we term MLLGA and MLLGB. MLLGA presented increased DOT1L phosphorylation, HOXA gene expression, CDK1 activity and phosphorylation of proteins involved in RNA metabolism, replication and DNA damage when compared to MLLGB and no KMT2A rearranged samples. MLLGA was particularly sensitive to 15 compounds including genotoxic drugs and inhibitors of mitotic kinases and inosine-5-monosphosphate dehydrogenase (IMPDH) relative to other cases. Intermediate-risk KMT2A-MLLT3 cases were mainly represented in a third group closer to MLLGA than to MLLGB. The expression of IMPDH2 and multiple nucleolar proteins was higher in MLLGA and correlated with the response to IMPDH inhibition in KMT2A rearranged leukaemia, suggesting a role of the nucleolar activity in sensitivity to treatment. In summary, our multilayer molecular profiling of AML with poor prognosis and KMT2A-MLLT3 karyotypes identified a phosphoproteomics signature that defines two biologically and phenotypically distinct groups of KMT2A rearranged leukaemia. These data provide a rationale for the potential development of specific therapies for AML patients characterised by the MLLGA phosphoproteomics signature identified in this study.

Proteomic and phosphoproteomic landscapes of acute myeloid leukemia

We have developed a deep-scale proteome and phosphoproteome database from 44 representative acute myeloid leukemia (AML) patients from the LAML TCGA dataset and 6 healthy bone marrow-derived controls. After confirming data quality, we orthogonally validated several previously undescribed features of AML revealed by the proteomic data. We identified examples of posttranscriptionally regulated proteins both globally (ie, in all AML samples) and also in patients with recurrent AML driver mutations. For example, samples with IDH1/2 mutations displayed elevated levels of the 2-oxoglutarate-dependent histone demethylases KDM4A/B/C, despite no changes in messenger RNA levels for these genes; we confirmed this finding in vitro. In samples with NPMc mutations, we identified several nuclear importins with posttranscriptionally increased protein abundance and showed that they interact with NPMc but not wild-type NPM1. We identified 2 cell surface proteins (CD180 and MRC1/CD206) expressed on AML blasts of many patients (but not healthy CD34+ stem/progenitor cells) that could represent novel targets for immunologic therapies and confirmed these targets via flow cytometry. Finally, we detected nearly 30 000 phosphosites in these samples; globally, AML samples were associated with the abnormal phosphorylation of specific residues in PTPN11, STAT3, AKT1, and PRKCD. FLT3-TKD samples were associated with increased phosphorylation of activating tyrosines on the cytoplasmic Src-family tyrosine kinases FGR and HCK and related signaling proteins. PML-RARA-initiated AML samples displayed a unique phosphorylation signature, and TP53-mutant samples showed abundant phosphorylation of serine-183 on TP53 itself. This publicly available database will serve as a foundation for further investigations of protein dysregulation in AML pathogenesis.

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemic cells with diverse mutation spectra, which eventually leads to disease relapse. This genetic heterogeneity drives the activation of complex signaling pathways that is reflected at the protein level. This diversity makes it difficult to treat AML with targeted therapy, requiring custom patient treatment protocols tailored to each individual's leukemia. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify genomic signatures that could predict patient-specific drug responses. However, there are inherent weaknesses in using only genetic and transcriptomic measurements as surrogates of drug response, particularly the absence of direct information about phosphorylation-mediated signal transduction. As a member of the Clinical Proteomic Tumor Analysis Consortium, we have extended the molecular characterization of this cohort by collecting proteomic and phosphoproteomic measurements from a subset of these patient samples (38 in total) to evaluate the hypothesis that proteomic signatures can improve the ability to predict response to 26 drugs in AML ex vivo samples. In this work we describe our systematic, multi-omic approach to evaluate proteomic signatures of drug response and compare protein levels to other markers of drug response such as mutational patterns. We explore the nuances of this approach using two drugs that target key pathways activated in AML: quizartinib (FLT3) and trametinib (Ras/MEK), and show how patient-derived signatures can be interpreted biologically and validated in cell lines. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to assess drug sensitivity in AML.

eEF2K Activity Determines Synergy to Cotreatment of Cancer Cells With PI3K and MEK Inhibitors

PI3K-mammalian target of rapamycin and MAPK/ERK kinase (MEK)/mitogen-activated protein kinase (MAPK) are the most frequently dysregulated signaling pathways in cancer. A problem that limits the success of therapies that target individual PI3K-MAPK members is that these pathways converge to regulate downstream functions and often compensate each other, leading to drug resistance and transient responses to therapy. In order to overcome resistance, therapies based on cotreatments with PI3K/AKT and MEK/MAPK inhibitors are now being investigated in clinical trials, but the mechanisms of sensitivity to cotreatment are not fully understood. Using LC-MS/MS-based phosphoproteomics, we found that eukaryotic elongation factor 2 kinase (eEF2K), a key convergence point downstream of MAPK and PI3K pathways, mediates synergism to cotreatment with trametinib plus pictilisib (which target MEK1/2 and PI3Kα/δ, respectively). Inhibition of eEF2K by siRNA or with a small molecule inhibitor reversed the antiproliferative effects of the cotreatment with PI3K plus MEK inhibitors in a cell model-specific manner. Systematic analysis in 12 acute myeloid leukemia cell lines revealed that eEF2K activity was increased in cells for which PI3K plus MEKi cotreatment is synergistic, while PKC potentially mediated resistance to such cotreatment. Together, our study uncovers eEF2K activity as a key mediator of responses to PI3Ki plus MEKi and as a potential biomarker to predict synergy to cotreatment in cancer cells.

Targeting the lysine-specific demethylase 1 rewires kinase networks and primes leukemia cells for kinase inhibitor treatment

Most tumor types either fail to respond or become resistant to kinase inhibitors, often because of compensatory prosurvival pathways in the cancer cell's broader signaling circuitry. Here, we found that intrinsic resistance to kinase inhibitors in cultured primary acute myeloid leukemia (AML) cells may be overcome by reshaping kinase networks into topologies that confer drug sensitivity. We identified several antagonists of chromatin-modifying enzymes that sensitized AML cell lines to kinase inhibitors. Of these, we confirmed that inhibitors of the lysine-specific demethylase (LSD1; also known as KDM1A) rewired kinase signaling in AML cells in a way that increased the activity of the kinase MEK and that broadly suppressed the activity of other kinases and feedback loops. As a result, AML cell lines and about half of primary human AML samples were primed for sensitivity to the MEK inhibitor trametinib. Primary human cells with KRAS mutations and those with high MEK pathway activity were the best responders to sequential treatment with LSD1 inhibitors then trametinib, whereas those with NRAS mutations and high mTOR activity were poor responders. Overall, our study reveals the MEK pathway as a mechanism of resistance to LSD1 inhibitors in AML and shows a way to modulate kinase network circuitry to potentially overcome therapeutic resistance to kinase inhibitors.

Targeting AML at the intersection of epigenetics and signaling

Mutations in multiple cancers may synergize to alter the cellular epigenetic and transcriptional state and corrupt key signaling pathways. In this issue of Science Signaling, Pedicona et al. illustrate how the two processes intersect to regulate cellular differentiation in acute myeloid leukemia (AML) and show how inhibition of epigenetic regulators promotes sensitivity to kinase inhibitors.

Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies

Protein kinase inhibitors are amongst the most successful cancer treatments, but targetable kinases activated by genomic abnormalities are rare in T cell acute lymphoblastic leukemia. Nevertheless, kinases can be activated in the absence of genetic defects. Thus, phosphoproteomics can provide information on pathway activation and signaling networks that offer opportunities for targeted therapy. Here, we describe a mass spectrometry-based global phosphoproteomic profiling of 11 T cell acute lymphoblastic leukemia cell lines to identify targetable kinases. We report a comprehensive dataset consisting of 21,000 phosphosites on 4,896 phosphoproteins, including 217 kinases. We identify active Src-family kinases signaling as well as active cyclin-dependent kinases. We validate putative targets for therapy ex vivo and identify potential combination treatments, such as the inhibition of the INSR/IGF-1R axis to increase the sensitivity to dasatinib treatment. Ex vivo validation of selected drug combinations using patient-derived xenografts provides a proof-of-concept for phosphoproteomics-guided design of personalized treatments.

Implementation of Clinical Phosphoproteomics and Proteomics for Personalized Medicine

The identification of biomarkers for companion diagnostics is revolutionizing the development of treatments tailored to individual patients in different disease areas including cancer. Precision medicine is most frequently based on the detection of genomic markers that correlate with the efficacy of selected targeted therapies. However, since nongenetic mechanisms also contribute to disease biology, there is a considerable interest of using proteomic techniques as additional source of biomarkers to personalize therapies. In this chapter, we describe label-free mass spectrometry methods for proteomic and phosphoproteomic analysis compatible with routine analysis of clinical samples. We also outline bioinformatic pipelines based on statistical learning that use these proteomics datasets as input to quantify kinase activities and predict drug responses in cancer cells.

Targeted therapy for LIMD1-deficient non-small cell lung cancer subtypes

An early event in lung oncogenesis is loss of the tumour suppressor gene LIMD1 (LIM domains containing 1); this encodes a scaffold protein, which suppresses tumorigenesis via a number of different mechanisms. Approximately 45% of non-small cell lung cancers (NSCLC) are deficient in LIMD1, yet this subtype of NSCLC has been overlooked in preclinical and clinical investigations. Defining therapeutic targets in these LIMD1 loss-of-function patients is difficult due to a lack of 'druggable' targets, thus alternative approaches are required. To this end, we performed the first drug repurposing screen to identify compounds that confer synthetic lethality with LIMD1 loss in NSCLC cells. PF-477736 was shown to selectively target LIMD1-deficient cells in vitro through inhibition of multiple kinases, inducing cell death via apoptosis. Furthermore, PF-477736 was effective in treating LIMD1-/- tumours in subcutaneous xenograft models, with no significant effect in LIMD1+/+ cells. We have identified a novel drug tool with significant preclinical characterisation that serves as an excellent candidate to explore and define LIMD1-deficient cancers as a new therapeutic subgroup of critical unmet need.

Activating mutations in BRAF disrupt the hypothalamo-pituitary axis leading to hypopituitarism in mice and humans

Germline mutations in BRAF and other components of the MAPK pathway are associated with the congenital syndromes collectively known as RASopathies. Here, we report the association of Septo-Optic Dysplasia (SOD) including hypopituitarism and Cardio-Facio-Cutaneous (CFC) syndrome in patients harbouring mutations in BRAF. Phosphoproteomic analyses demonstrate that these genetic variants are gain-of-function mutations leading to activation of the MAPK pathway. Activation of the MAPK pathway by conditional expression of the BrafV600E/+ allele, or the knock-in BrafQ241R/+ allele (corresponding to the most frequent human CFC-causing mutation, BRAF p.Q257R), leads to abnormal cell lineage determination and terminal differentiation of hormone-producing cells, causing hypopituitarism. Expression of the BrafV600E/+ allele in embryonic pituitary progenitors leads to an increased expression of cell cycle inhibitors, cell growth arrest and apoptosis, but not tumour formation. Our findings show a critical role of BRAF in hypothalamo-pituitary-axis development both in mouse and human and implicate mutations found in RASopathies as a cause of endocrine deficiencies in humans.

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of >400 drugs based on their anti-proliferative efficacy in cancer cells. To reduce noise and increase predictive robustness, instead of individual features, DRUML uses internally normalized distance metrics of drug response as features for ML model generation. DRUML is trained using in-house proteomics and phosphoproteomics data derived from 48 cell lines, and it is verified with data comprised of 53 cellular models from 12 independent laboratories. We show that DRUML predicts drug responses in independent verification datasets with low error (mean squared error < 0.1 and mean Spearman's rank 0.7). In addition, we demonstrate that DRUML predictions of cytarabine sensitivity in clinical leukemia samples are prognostic of patient survival (Log rank p < 0.005). Our results indicate that DRUML accurately ranks anti-cancer drugs by their efficacy across a wide range of pathologies.

His452Tyr polymorphism in the human 5-HT2A receptor affects clozapine-induced signaling networks revealed by quantitative phosphoproteomics

Antipsychotic drugs remain the current standard for schizophrenia treatment. Although they directly recognize the orthosteric binding site of numerous monoaminergic G protein-coupled receptors (GPCRs), these drugs, and particularly second-generation antipsychotics such as clozapine, all have in common a very high affinity for the serotonin 5-HT_2A receptor (5-HT_2AR). Using classical pharmacology and targeted signaling pathway assays, previous findings suggest that clozapine and other atypical antipsychotics behave principally as 5-HT_2AR neutral antagonists and/or inverse agonists. However, more recent findings showed that antipsychotics may also behave as pathway-specific agonists. Reversible phosphorylation is a common element in multiple signaling networks. Combining a quantitative phosphoproteomic method with signaling network analysis, we tested the effect of clozapine treatment on the overall level of protein phosphorylation and signal transduction cascades in vitro in mammalian cell lines induced to express either the human 5-HT_2AR or the H452Y variant of the gene encoding the 5-HT_2AR receptor. This naturally occurring variation within the 5-HT_2AR gene was selected because it has been repeatedly associated with schizophrenia patients who do not respond to clozapine treatment. Our data show that short time exposure (5 or 10 min) to clozapine (10^-5 M) led to phosphorylation of numerous signaling components of pathways involved in processes such as endocytosis, ErbB signaling, insulin signaling or estrogen signaling. Cells induced to express the H452Y variant showed a different basal phosphoproteome, with increases in the phosphorylation of mTOR signaling components as a translationally relevant example. However, the effect of clozapine on the functional landscape of the phosphoproteome was significantly reduced in cells expressing the 5-HT_2AR-H452Y construct. Together, these findings suggest that clozapine behaves as an agonist inducing phosphorylation of numerous pathways downstream of the 5-HT_2AR, and that the single nucleotide polymorphism encoding 5-HT_2AR-H452Y affects these clozapine-induced phosphorylation-dependent signaling networks.

PARP-1 activation after oxidative insult promotes energy stress-dependent phosphorylation of YAP1 and reduces cell viability

Poly(ADP-ribose) polymerase 1 (PARP-1) is a nuclear enzyme that catalyze the transfer of ADP-ribose units from NAD+ to several target proteins involved in cellular stress responses. Using WRL68 (HeLa derivate) cells, we previously showed that PARP-1 activation induced by oxidative stress after H2O2 treatment lead to depletion of cellular NAD+ and ATP, which promoted cell death. In this work, LC-MS/MS-based phosphoproteomics in WRL68 cells showed that the oxidative damage induced by H2O2 increased the phosphorylation of YAP1, a transcriptional co-activator involved in cell survival, and modified the phosphorylation of other proteins involved in transcription. Genetic or pharmacological inhibition of PARP-1 in H2O2-treated cells reduced YAP1 phosphorylation and degradation and increased cell viability. YAP1 silencing abrogated the protective effect of PARP-1 inhibition, indicating that YAP1 is important for the survival of WRL68 cells exposed to oxidative damage. Supplementation of NAD+ also reduced YAP1 phosphorylation, suggesting that the loss of cellular NAD+ caused by PARP-1 activation after oxidative treatment is responsible for the phosphorylation of YAP1. Finally, PARP-1 silencing after oxidative treatment diminished the activation of the metabolic sensor AMPK. Since NAD+ supplementation reduced the phosphorylation of some AMPK substrates, we hypothesized that the loss of cellular NAD+ after PARP-1 activation may induce an energy stress that activates AMPK. In summary, we showed a new crucial role of PARP-1 in the response to oxidative stress in which PARP-1 activation reduced cell viability by promoting the phosphorylation and degradation of YAP1 through a mechanism that involves the depletion of NAD+.

Integrated phosphoproteomics and transcriptional classifiers reveal hidden RAS signaling dynamics in multiple myeloma

A major driver of multiple myeloma (MM) is thought to be aberrant signaling, yet no kinase inhibitors have proven successful in the clinic. Here, we employed an integrated, systems approach combining phosphoproteomic and transcriptome analysis to dissect cellular signaling in MM to inform precision medicine strategies. Unbiased phosphoproteomics initially revealed differential activation of kinases across MM cell lines and that sensitivity to mammalian target of rapamycin (mTOR) inhibition may be particularly dependent on mTOR kinase baseline activity. We further noted differential activity of immediate downstream effectors of Ras as a function of cell line genotype. We extended these observations to patient transcriptome data in the Multiple Myeloma Research Foundation CoMMpass study. A machine-learning-based classifier identified surprisingly divergent transcriptional outputs between NRAS- and KRAS-mutated tumors. Genetic dependency and gene expression analysis revealed mutated Ras as a selective vulnerability, but not other MAPK pathway genes. Transcriptional analysis further suggested that aberrant MAPK pathway activation is only present in a fraction of RAS-mutated vs wild-type RAS patients. These high-MAPK patients, enriched for NRAS Q61 mutations, have inferior outcomes, whereas RAS mutations overall carry no survival impact. We further developed an interactive software tool to relate pharmacologic and genetic kinase dependencies in myeloma. Collectively, these predictive models identify vulnerable signaling signatures and highlight surprising differences in functional signaling patterns between NRAS and KRAS mutants invisible to the genomic landscape. These results will lead to improved stratification of MM patients in precision medicine trials while also revealing unexplored modes of Ras biology in MM.

A systematic molecular and pharmacologic evaluation of AKT inhibitors reveals new insight into their biological activity

BACKGROUND

AKT, a critical effector of the phosphoinositide 3-kinase (PI3K) signalling cascade, is an intensely pursued therapeutic target in oncology. Two distinct classes of AKT inhibitors have been in clinical development, ATP-competitive and allosteric. Class-specific differences in drug activity are likely the result of differential structural and conformational requirements governing efficient target binding, which ultimately determine isoform-specific potency, selectivity profiles and activity against clinically relevant AKT mutant variants.

METHODS

We have carried out a systematic evaluation of clinical AKT inhibitors using in vitro pharmacology, molecular profiling and biochemical assays together with structural modelling to better understand the context of drug-specific and drug-class-specific cell-killing activity.

RESULTS

Our data demonstrate clear differences between ATP-competitive and allosteric AKT inhibitors, including differential effects on non-catalytic activity as measured by a novel functional readout. Surprisingly, we found that some mutations can cause drug resistance in an isoform-selective manner despite high structural conservation across AKT isoforms. Finally, we have derived drug-class-specific phosphoproteomic signatures and used them to identify effective drug combinations.

CONCLUSIONS

These findings illustrate the utility of individual AKT inhibitors, both as drugs and as chemical probes, and the benefit of AKT inhibitor pharmacological diversity in providing a repertoire of context-specific therapeutic options.

Reconstructing kinase network topologies from phosphoproteomics data reveals cancer-associated rewiring

Understanding how oncogenic mutations rewire regulatory-protein networks is important for rationalizing the mechanisms of oncogenesis and for individualizing anticancer treatments. We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can be used to infer >1,500 kinase-kinase interactions and devised algorithms that can reconstruct kinase network topologies from these phosphoproteomics data. Application of our methods to primary acute myeloid leukemia and breast cancer tumors quantified the relationship between kinase expression and activity, and enabled the identification of hitherto unknown kinase network topologies associated with drug-resistant phenotypes or specific genetic mutations. Using orthogonal methods we validated that PIK3CA wild-type cells adopt MAPK-dependent circuitries in breast cancer cells and that the kinase TTK is important in acute myeloid leukemia. Our phosphoproteomic signatures of network circuitry can identify kinase topologies associated with both phenotypes and genotypes of cancer cells.

Proteome and Phosphoproteome Changes Associated with Prognosis in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a hematological cancer that mainly affects the elderly. Although complete remission (CR) is achieved for the majority of the patients after induction and consolidation therapies, nearly two-thirds relapse within a short interval. Understanding biological factors that determine relapse has become of major clinical interest in AML. We utilized liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify the protein changes and protein phosphorylation events associated with AML relapse in primary cells from 41 AML patients at time of diagnosis. Patients were defined as relapse-free if they had not relapsed within a five-year clinical follow-up after AML diagnosis. Relapse was associated with increased expression of RNA processing proteins and decreased expression of V-ATPase proteins. We also observed an increase in phosphorylation events catalyzed by cyclin-dependent kinases (CDKs) and casein kinase 2 (CSK2). The biological relevance of the proteome findings was supported by cell proliferation assays using inhibitors of V-ATPase (bafilomycin), CSK2 (CX-4945), CDK4/6 (abemaciclib) and CDK2/7/9 (SNS-032). While bafilomycin preferentially inhibited the cells from relapse patients, the kinase inhibitors were less efficient in these cells. This suggests that therapy against the upregulated kinases could also target the factors inducing their upregulation rather than their activity. This study, therefore, presents markers that could help predict AML relapse and direct therapeutic strategies.

Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action

BACKGROUND

Post-translational modification (PTM) crosstalk is a young research field. However, there is now evidence of the extraordinary characterization of the different proteoforms and their interactions in a biological environment that PTM crosstalk studies can describe. Besides gene expression and phosphorylation profiling of acute myeloid leukemia (AML) samples, the functional combination of several PTMs that might contribute to a better understanding of the complexity of the AML proteome remains to be discovered.

OBJECTIVE

By reviewing current workflows for the simultaneous enrichment of several PTMs and bioinformatics tools to analyze mass spectrometry (MS)-based data, our major objective is to introduce the PTM crosstalk field to the AML research community.

RESULTS

After an introduction to PTMs and PTM crosstalk, this review introduces several protocols for the simultaneous enrichment of PTMs. Two of them allow a simultaneous enrichment of at least three PTMs when using 0.5-2 mg of cell lysate. We have reviewed many of the bioinformatics tools used for PTM crosstalk discovery as its complex data analysis, mainly generated from MS, becomes challenging for most AML researchers. We have presented several non-AML PTM crosstalk studies throughout the review in order to show how important the characterization of PTM crosstalk becomes for the selection of disease biomarkers and therapeutic targets.

CONCLUSION

Herein, we have reviewed the advances and pitfalls of the emerging PTM crosstalk field and its potential contribution to unravel the heterogeneity of AML. The complexity of sample preparation and bioinformatics workflows demands a good interaction between experts of several areas.

Heterogeneity in refractory acute myeloid leukemia

Successful clinical remission to therapy for acute myeloid leukemia (AML) is required for long-term survival to be achieved. Despite trends in improved survival due to better supportive care, up to 40% of patients will have refractory disease, which has a poorly understood biology and carries a dismal prognosis. The development of effective treatment strategies has been hindered by a general lack of knowledge about mechanisms of chemotherapy resistance. Here, through transcriptomic analysis of 154 cases of treatment-naive AML, three chemorefractory patient groups with distinct expression profiles are identified. A classifier, four key refractory gene signatures (RG4), trained based on the expression profile of the highest risk refractory patients, validated in an independent cohort (n = 131), was prognostic for overall survival (OS) and refined an established 17-gene stemness score. Refractory subpopulations have differential expression in pathways involved in cell cycle, transcription, translation, metabolism, and/or stem cell properties. Ex vivo drug sensitivity to 122 small-molecule inhibitors revealed effective group-specific targeting of pathways among these three refractory groups. Gene expression profiling by RNA sequencing had a suboptimal ability to correctly predict those individuals resistant to conventional cytotoxic induction therapy, but could risk-stratify for OS and identify subjects most likely to have superior responses to a specific alternative therapy. Such personalized therapy may be studied prospectively in clinical trials.

Illuminating the dark phosphoproteome

Protein phosphorylation is a major regulator of protein function and biological outcomes. This was first recognized through functional biochemical experiments, and in the past decade, major technological advances in mass spectrometry have enabled the study of protein phosphorylation on a global scale. This rapidly growing field of phosphoproteomics has revealed that more than 100,000 distinct phosphorylation events occur in human cells, which likely affect the function of every protein. Phosphoproteomics has improved the understanding of the function of even the most well-characterized protein kinases by revealing new downstream substrates and biology. However, current biochemical and bioinformatic approaches have only identified kinases for less than 5% of the phosphoproteome, and functional assignments of phosphosites are almost negligible. Notably, our understanding of the relationship between kinases and their substrates follows a power law distribution, with almost 90% of phosphorylation sites currently assigned to the top 20% of kinases. In addition, more than 150 kinases do not have a single known substrate. Despite a small group of kinases dominating biomedical research, the number of substrates assigned to a kinase does not correlate with disease relevance as determined by pathogenic human mutation prevalence and mouse model phenotypes. Improving our understanding of the substrates targeted by all kinases and functionally annotating the phosphoproteome will be broadly beneficial. Advances in phosphoproteomics technologies, combined with functional screening approaches, should make it feasible to illuminate the connectivity and functionality of the entire phosphoproteome, providing enormous opportunities for discovering new biology, therapeutic targets, and possibly diagnostics.

Therapeutic Targeting of mTOR in T-Cell Acute Lymphoblastic Leukemia: An Update

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive blood malignancy that arises from the clonal expansion of transformed T-cell precursors. Although T-ALL prognosis has significantly improved due to the development of intensive chemotherapeutic protocols, primary drug-resistant and relapsed patients still display a dismal outcome. In addition, lifelong irreversible late effects from conventional therapy are a growing problem for leukemia survivors. Therefore, novel targeted therapies are required to improve the prognosis of high-risk patients. The mechanistic target of rapamycin (mTOR) is the kinase subunit of two structurally and functionally distinct multiprotein complexes, which are referred to as mTOR complex 1 (mTORC1) and mTORC2. These two complexes regulate a variety of physiological cellular processes including protein, lipid, and nucleotide synthesis, as well as autophagy in response to external cues. However, mTOR activity is frequently deregulated in cancer, where it plays a key oncogenetic role driving tumor cell proliferation, survival, metabolic transformation, and metastatic potential. Promising preclinical studies using mTOR inhibitors have demonstrated efficacy in many human cancer types, including T-ALL. Here, we highlight our current knowledge of mTOR signaling and inhibitors in T-ALL, with an emphasis on emerging evidence of the superior efficacy of combinations consisting of mTOR inhibitors and either traditional or targeted therapeutics.