Proteomics-based prediction of clinical response in acute myeloid leukemia

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.

Pharmacometabolomics identifies dodecanamide and leukotriene B4 dimethylamide as a predictor of chemosensitivity for patients with acute myeloid leukemia treated with cytarabine and anthracycline

Clinical responses to standard cytarabine plus anthracycline regimen in acute myeloid leukemia (AML) are heterogeneous and there is an unmet need for biological predictors of response to this regimen. Here, we applied a pharmacometabolomics approach to identify potential biomarkers associated with response to this regimen in AML patients. Based on clinical response the enrolled 82 patients were subdivided into two groups: complete remission(CR) responders (n=42) and non-responders (n=40). Metabolic profiles of pre-treatment serum from patients were analyzed by ultra-high performance liquid chromatography coupled with mass spectrometry and the metabolic differences between the two groups were investigated by multivariate statistical analysis. A metabolite panel containing dodecanamide and leukotriene B4 dimethylamide (LTB4-DMA) had the power capacity to differentiate the two groups of patients, yielding an area under the receiver operating characteristic of 0.945 (85.2% sensitivity and 88.9% specificity) in the training set and 0.944(84.6% sensitivity and 80.0% specificity) in the test set. The patients with high levels of LTB4-DMA and low amounts of dodecanamide had good sensitivity to chemotherapeutic agents. The possible reasons were that dodecanamide was produced by leukemic cells as a lipolytic factor to fuel their growth with a potential role in drug resistance and LTB4-DMA was a potent leukotriene B4 antagonist that could be applicable in the treatment of AML. These preliminary results demonstrates the feasibility of relating chemotherapy responses with pre-treatment metabolic profiles of AML patients, and pharmacometabolomics may be a useful tool to select patients that are more likely to benefit from cytarabine plus anthracycline chemotherapy.

Molecular biomarkers in acute myeloid leukemia

Acute myeloid leukemia (AML) is the most common acute leukemia in adults. The pathophysiology of this disease is just beginning to be understood at the cellular and molecular level, and currently cytogenetic markers are the most important for risk stratification and treatment of AML patients. However, with the advent of new technologies, the detection of other molecular markers such as point mutations and characterization of epigenetic and proteomic profiles, have begun to play an important role in how the disease is approached. Recent evidence shows that the identification of new AML biomarkers contributes to a better understanding of the molecular basis of the disease, is significantly useful in screening, diagnosis, prognosis and monitoring of AML, as well as the possibility of predicting each individual's response to treatment. This review summarizes the most relevant molecular (genetic, epigenetic, and protein) biomarkers associated with acute myeloid leukemia and discusses their clinical importance in terms of risk prediction, diagnosis and prognosis.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Exploratory proteomic analysis of hypobaric hypoxia and acute mountain sickness in humans

Our objective in this exploratory study was to identify novel biomarkers of importance for acute mountain sickness (AMS) using discovery-based proteomic methods. Peripheral blood samples were collected and AMS symptoms were assessed in 20 healthy volunteers prior to [-15 h (baseline) and 0 h; 1,609 m; barometric pressure = 625 mmHg] and after a 9-h exposure to hypobaric hypoxia (9 h; 4,875 m; barometric pressure = 425 mmHg). AMS status was assessed using the Lake Louise Questionnaire. Plasma samples were pooled according to AMS status at each time point. Protein composition of the samples was determined by a GeLC-MS/MS approach using two analytical platforms (LTQ-XL linear ion trap mass spectrometer and a LTQ-FT ultra hybrid mass spectrometer) for technical replication. Spectral counting was used to make semiquantitative comparisons of protein abundance between AMS-susceptible (AMS) and AMS-resistant (AMS·R) subjects with exposure to hypobaric hypoxia. After 9 h of hypoxia, the abundance of proteins with antioxidant properties (i.e., peroxiredoxin 6, glutathione peroxidase, and sulfhydryl oxidase 1) rose in AMS but not AMS·R. Our exploratory analyses suggest that exposure to hypobaric hypoxia enhances enzymatic antioxidant systems in AMS vs. AMS·R, which, we propose, may be an overcompensation for hypoxia-induced oxidant production. On the basis of our findings we 1) speculate that quenching oxidant activity may have adverse downstream effects that are of pathophysiological importance for AMS such as interrupting oxidant-sensitive cell signaling and gene transcription and 2) question the existing assumption that increased oxidant production in AMS is pathological.

A new frontier in personalized cancer therapy: mapping molecular changes

Mutations in the genome of a normal cell can affect the function of its many genes and pathways. These alterations could eventually transform the cell from a normal to a malignant state by allowing an uncontrolled proliferation of the cell and formation of a cancer tumor. Each tumor in an individual patient can have hundreds of mutated genes and perturbed pathways. Cancers clinically presenting as the same type or subtype could potentially be very different at the molecular level and thus behave differently in response to therapy. The challenge is to distinguish the key mutations driving the cancer from the background of mutational noise and find ways to effectively target them. The promise is that such a molecular approach to classifying cancer will lead to better diagnostic, prognostic and personalized treatment strategies. This article provides an overview of advances in the molecular characterization of cancers and their applications in therapy.

Proteomics for identifying mechanisms and biomarkers of drug resistance in cancer

A major problem in chemotherapy of cancer patients is drug resistance as well as unpredictable response to treatment. During chemotherapy, multiple alterations of genetics and epigenetics that contribute to chemoresistance take place, eventually impacting on disease outcome. A more complex picture of the mechanisms of drug resistance is now emerging through application of high-throughput proteomics technology. We have entered an exciting time where proteomics are being applied to characterize the mechanisms of drug resistance, and to identify biomarkers for predicting response to chemotherapy, thereby leading to personalized therapeutic strategies of cancer patients. Comparative proteomics have identified a large number of differentially expressed proteins associated with chemoresistance. Although roles and mechanisms of such proteins in chemoresistance need to be further proved, at least some of them may be potential biomarkers for predicting chemotherapeutic response. Herein, we review the recent advancements on proteomic investigation of chemoresistance in human cancer, and emphasize putative biomarkers for predicting chemotherapeutic response and possible mechanisms of chemoresistance identified through proteomic approaches. Suggested avenues for future work are discussed.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Mass spectrometry-based proteomics and its potential use in haematological research

In the last decade proteomics has made great progress reaching throughput and comprehensiveness comparable to genomics technologies. Mass spectrometry plays a key role in proteomics and has become an indispensable method for molecular and cellular biology because many cellular changes in response to internal or external stimuli can only be detected at the proteome level. Furthermore, different from genomics which depends on the availability of DNA or RNA, proteomics is not restricted to cellular samples, but also allows the analysis of biological fluids like serum, plasma or urine. This article provides an overview of the recent developments in proteomics techniques useful for haematological research.