Investigation Of Serum Peptide Pattern For Acute Leukemia Diagnosis And Therapeutic Efficacy Evaluation

Acute leukemia (AL) is a malignant blood disease with abnormal hematopoietic stem cells, which can cause severe health problems, even death. The hematopoietic cells with gene defects in AL patients lost the ability of normal differentiation and response to normal regulators of proliferation. Finally, many primary hematopoietic stem cells cumulate in the bone marrow, peripheral blood and other organs, which inhibit normal hematopoietic cells growth and cause a series of clinical manifestation, such as anemia, haemorrhage, infection, hepatosplenomegaly and lymphadenectasis. Now the diagnosis of AL can be made on the bone marrow analysis, including morphology, immunology, cytogenetics and molecular genetics analysis. After treatment, the diagnostic methods mentioned above also can be used for the evaluation of early therapeutic efficacy that is essential for further treatment and prognostic assessment. However, AL patients should undergo bone marrow aspiration under local anesthesia before analysis, which is invasive, time-consuming and risky, so a minimally invasive, fast and sensitive approach for serum diagnosis and evaluation is necessary.The characteristics of serum examination are minimally invasive, low cost, easy acquiring and processing. Also the serum protein level under disease state is different from the level in healthy state. Thus, serum is a good specimen to be generally used in disease marker research. Serum peptide pattern is a novel diagnostic method, in which mass spectrometry is used to generate serum peptide profiles, and the diagnosis will be given based on the peptide pattern difference by bioinformatics software. The researchers have obtained a lot of exciting results when this method was applied for the investigation in tumor diagnosis. In 2002, a paper named "Use of proteomic patterns in serum to identify ovarian cancer" was published in Lancet journal. In this paper, the serum peptide pattern was used for ovarian cancer diagnosis. They analyzed the peptide pattern of healthy control group and disease group to diagnose ovarian cancer by mass spectrometry and bioinformatics software. The results showed that all 55 ovarian cancer patients were correctly diagnosis, and 18 of 55 cases were stage I ovarian cancer patients. The sensitivity, specificity and positive predictive value is 100%, 95%,94%, respectively. It suggested that this method was better than traditional detection of CA125 and was also very effective in the diagnosis of early stage ovarian cancer. Later, several papers about serum peptide pattern for tumor diagnosis were published, such as 2006, Villanueva et al published their research in bladder cancer, breast cancer, and prostate cancer diagnosis on The Journal of Clinical Investigation. At the end of 2006, a comment on this paper was given on Nature. In the comment, the author shows a positive attitude toward the development and application of this serum peptide technique in future. Also, there is another paper about serum peptide technique used for metastatic thyroid cancer diagnosis published by Villanueva et al on the Molecular & Cellular Proteomics journal. Additionally, serum peptide technique related papers were also published on the Clinical Cancer Research, Journal of Clinical Oncology and Clinical Chemistry. It is worth mentioning that this technique not only can be used in tumor diagnosis, but also used in other disease research, such as tuberculosis. In 2006 Lancet, a paper "Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum" was published. The results revealed that serum peptide technique obtained more than 95% specificity and sensitivity in diagnosis of tuberculosis, which is better than the traditional diagnostic method. All of these results indicate that human serum peptides, especially low molecular weight peptides contain important information for tumor diagnosis. It is thus more useful and helpful to do research in serum peptide patterns than in traditional single markerSerum protein and peptide isolation is the key point in proteomics research. 2-DE is a typical protein isolation technique in proteomics research. It can isolate intact protein from complex according to their physical properties, eg, isoelectric point and molecular weight. But it requires large sample quantities, has a limited dynamic range for protein detection, is poorly reproducible and labor intensive, thus it is not fit for clinical diagnosis. Recently, protein chip has been applied in serum peptide research. The sample without preparation can be used for detection directly. However, this advantage is also the disadvantage of this method. Because the samples can not be further identified. Also, protein chip is so sophisticated and high cost that limits its application. Given high-resolution MALDI-TOF-MS has been developed for tumor research, a variety of protein/peptide isolation methods can be combined to overcome the problems of protein chip. Moreover, the emergence of high resolution and sensitivity FT-ICR-MS makes the serum peptide identification to be possible. Magnetic beads based technique is newly developed for serum peptide preparation. This method uses different chemical chromatographic surfaces on the out layer of magnetic beads to selective purify certain subsets of proteins/peptides. Since magnetic beads have the characteristics of large surface area, high binding capacity, high efficiency, easy processing and good reproducibility, it has been combined with MALDI-TOF-MS detection and utilized in disease proteomic research.In this study, magnetic beads and high-resolution MALDI-TOF-MS were used as the main techniques for the research in serum peptide pattern of acute leukemia. The evaluation about stability and reproducibility of this technique system was performed at beginning. The results showed this system was stable and accord with the standard. We further used this system to analyze AL group and healthy control group sera, and obtained the serum peptide profiles. After analysis by bioinformatics software Biosun_MS (SVM algorithm and t-test), a diagnostic model based on serum peptide pattern was set up for diagnosing acute leukemia. This model achieved 100% specificity and 97% sensitivity. Further intensity analysis of 55 features (P<0.001) in primary AL, AL with hematologic complete remission, AL with molecular remission and healthy controls, two peptides m/z 1865.13 and 1778.05 were found decreased in their relative intensity with the increase of remission degree. In M3-AL, their relative intensities also decreased and were close to normal state after molecular remission. With FT-ICR-MS detection, both the peptides were identified as fragments of complement C3f. Furthermore, this system was also applied for the assessment of treatment efficacy in acute leukemia. Through analyzing primary AL and their hematologic complete remission sera, we obtained the serum peptide profiles. After analysis by bioinformatics software Biosun_MS (SVM algorithm and t-test), a diagnostic model based on serum peptide pattern was set up for the assessment of treatment efficacy in acute leukemia, and got 100% sensitivity and 90% specificity.These results manifested that serum peptide pattern could reflect the pathological state of disease, which will be the evidence for our further study. The conclusions of our investigation were as following:(1) A model for acute leukemia diagnosis and a model for treatment efficacy evaluation in acute leukemia have been built, respectively. Moreover, two peptides were found to be related with minimal residual disease monitoring. (2) 7 feature peptide sequences we got in this research could be helpful for further discussion about mechanisms of acute leukemia. The novelty of this study is the application of serum peptide techniques in acute leukemia research as well as investigating and discussing the potential role of serum peptide technique in minimal residual disease monitoring and therapeutic evaluation.