Classification Of Acute Myelogenous Leukemia Research Articles

New Approaches for the Treatment of AML beyond the 7+3 Regimen: Current Concepts and New Approaches

Fifty years have passed since the development of the first chemotherapy regimen for treating acute myelogenous leukemia (AML), with the approval in 1973 of the cytarabine daunorubicin (7+3) regimen. Until recently, patients diagnosed with AML had very limited treatment options and depended primarily on chemotherapy in combinations, doses, or schedules of the same drugs. Patients with advanced age, comorbidities, or relapsed or refractory disease were left with no effective options for treatment. New advances in the understanding of the biology and the molecular and genetic changes associated with leukemogenesis, as well as recent advances in drug development, have resulted in the introduction over the last few years of novel therapeutic agents and approaches to the treatment of AML as well as a new classification of the disease. In this article, we will discuss the new classification of AML; the mechanisms, actions, and indications of the new targeted therapies; the chemotherapy combinations; and the potential role of cellular therapies as new treatment options for this terrible disease.

Comparison of classification techniques in the diagnosis of acute myelogenous leukemia

The leukemia blood cell discriminates from other blood cells by geometrical structure and cellular material by hematologist with microscope. In conventional color imaging system, the granular region in leukemia cells classify false negatively by experts due to micro geometrical and morphological changes in leukemia cell. Hence, a computer aided decision support system (CADSS) employs for automatic classification of leukemia blood cells. This paper gives the comparative study of various methods of classification of Acute Myelogenous Leukemia (AML) with improved accuracy and their results are compared. In this paper, the classification techniques such as Convolutional Neural Networks (CNN), Support Vector Machines (SVM), Fraction Black-Widow Optimized Neural Network (FB-NN), Deep CNN with Arithmetic Optimization and Hybrid Convolutional Bi-LSTM based RNN are made with blood microscopic images, in which according to measures, Deep CNN with Arithmetic Optimization has the best accuracy.

Acute Myelogenous Leukemia Detection using Circumventing Ant Colony Optimization based Convolutional Neural Network

Acute Myelogenous Leukemia (AML) is a type of disease associated with acute leukemia which is getting increased in both children’s and adults. AML falls under the category of cancer disease. The term acute in AML indicates rapid progression of disease in human body. The main challenge of medical field in vision of computer and multimedia is texture and color between various categories. The variation in texture and color attributes makes the classification task a tedious. Deep learning has shown its dazzling performance in various streams, which includes classification too. The objective of image classification is to differentiate the subcategories that belong to same basic-level category. The main objective of this paper is to propose bioinspired based on convolutional neural network to classify the microscopic blood images for AML. This paper has utilized bioinspired concept to extract the features more reliably. Bench mark performance metrics were chosen to evaluate the proposed classifier against the previous classifiers based on two parameters. The results indicate that the proposed classifiers has outperformed the previous works towards the classification of AML.

Classification of Acute Myelogenous Leukemia (AML M2 and AML M3) using Momentum Back Propagation from Watershed Distance Transform Segmented Images

This study uses image processing to analyze white blood cell with leukemia indicated that includes the identification, analysis of shapes and sizes, as well as white blood cell count indicated the symptoms of leukemia. A case study in this research was blood cells, from the type of leukemia Acute Myelogenous Leukemia (AML), M2 and M3 in particular. Image processing operations used for segmentation by utilizing the color conversion from RGB (Red, Green dab Blue) to obtain white blood cell candidates. Furthermore, the white blood cells candidates are separated by other cells with active contour without edge. WBC (White Blood Cell) results still have intersected or overlap condition. Watershed distance transform method can separate overlap of WBC. Furthermore, the separation of the nucleus from the cytoplasm using the HSI (Hue Saturation Intensity). The further characteristic extraction process is done by calculating the area WBC, WBC edge, roundness, the ratio of the nucleus, the mean and standard deviation of pixel intensities. The feature extraction results are used for training and testing in determining the classification of AML: M2 and M3 by using the momentum backpropagation algorithm. The classification process is done by testing the numeric data input from the feature extraction results that have been entered in the database. K-Fold validation is used to divide the amount of training data and to test the classification of AML M2 and M3. The experiment results of eight images trials, the result, was 94.285% per cell accuracy and 75% per image accuracy

Classification Of Acute Myelogenous Leukemia (AML) Based On Functionally Related Proteins Groups

BackgroundIn an era where the recognized heterogeneity of the pathophysiology of AML is increasing rapidly due to sequencing and other “omics” platforms, and where the number of available targeted therapeutics is also rapidly expanding, a means to individually match therapies to AML on a specific basis is needed. New targeted therapies modulate single pathways, so recognizing when a particular pathway is active is crucial, but mutations are rare within most of these pathways in AML. Furthermore pathway activation can arise by various means. Finally the interaction of multiple different activated pathways on the overall phenotype of a leukemic blast adds complexity. MethodsTo define the role of the pathway activation in AML we generated a custom made reverse phase protein array (RPPA) onto which were printed leukemia enriched (ficolled, CD3/CD19 depleted) cells from 511 newly diagnosed AML and 21 APL patients, including 49 with paired diagnosis and relapse samples. Both bone marrow (n=387) and peripheral blood (n=283) samples were used, with 140 cases having both. The RPPA was probed with 231 strictly validated antibodies (174 antibodies vs. total expression, 49 vs. phosphoproteins, 5 vs. cleaved forms, 3 vs. methylation sites). These proteins were divided on the basis of function into 21 Protein function groups (ProFnG) including: Apoptosis, Autophagy, Cell cycle, Creb, Cytoskeletal, Differentiation, Fli1, Hippo, Histone modifying, Hypoxia, Integrin & adhesion, MEK, P53, PI3K-AKT, PKC, SMAD, STAT, Transcription Ubiquitin and Wnt. ResultsEach ProFnGrp was analyzed to determine the optimal number of principal components (PrCp) and to identify noncontributory members, which were then discarded. Each PrCp (79 total) was then considered a variable and Hierarchical clustering was performed on continuous and binary signals (Sokal-Michener metric) (Figure 1). This defined 8 PrCp clusters and 8 patient groups(PatGp). Several categorical clinical features were unevenly associated with the PatGp including FAB (p=1.5e-12), WHO class (p=0.01), gender (p=0.03), Zubrod PS (p=0.005), antecedent hematological disorder (p=0.007), Cytogenetics (0.01), FLT3-ITD (p=0.003), Ras mutation (p=0.003). Likewise many continuous variables also correlated with PatGp: WBC (p=7e-14), %BM blast (p=2x10-16), % PB blast (p=2x10-16), Platelets (p=0.004), LDH (p=0.009), Albumin (p= 0.00001), Creatinine (p=0.007), CD13 (p=0.0002), CD33 (4.5xe-8), CD33 (1.1e-8). For all patients PatGp did not predict remission attainment. There was significant splay in overall survival and event free survival with median EFS durations ranging 52 , 100, 130 and 170 weeks ( p= 0.05) and in remission duration ranging from medians of 20- to 110 weeks. For intermediate cytogenetics Pat-Gps split into 4 with better outcomes (median OS 70-110 week, median RemDur 100-120 weeks) and 4 with worse outcomes (median OS 40-50 weeks, median RemDur 30-40 weeks). For unfavorable cytogenetics Pat-Gps also split into 4 with better outcomes (median OS 35-40 weeks, median RemDur 48-75 weeks) and 4 with worse outcomes (median OS 16-18 weeks, median RemDur 10-26 weeks). In a companion abstract we show the interaction between different protein functional groups. [Display omitted] ConclusionsAML could be classified based on protein functional groups. Although the classes were associated with cytogenetics the protein classifications gave prognostic information independent of cytogenetics and other traditional prognostic factors. Since this classification scheme is dependent on protein expression and functional activation states it may identify when particular pathways are being utilized and therefore be of use in triaging patients to targeted therapies. Disclosures:No relevant conflicts of interest to declare.

Proteomic Profiling of 150 Proteins in 511 Acute Myelogenous Leukemia (AML) Patient Samples Using Reverse Phase Proteins Arrays (RPPA) Reveals Recurrent Proteins Expression Signatures with Prognostic Implications

We previously demonstrated that protein expression signatures (ProExpSig), based on the activation state of cell cycle, apoptosis and signal transduction (STP) regulating proteins, existed and were prognostic in AML. With the goal of providing comprehensive proteomic based classification of AML we have now generated a RPPA using protein derived from the leukemia enriched fraction of 752 primary AML samples. Included are 695 samples from 511 newly diagnosed AML and 28 APL patients (403 Marrow (BM), 293 blood (PB) samples, 140 with concurrent PB and BM specimens), and 47 relapse (REL) samples from these same cases. Also present as controls are 10 cell lines, 11 normal PB, 11 CD34+ BM samples and 10 G-CSF primed CD34+ PB collections. Samples are printed as 5 serial 1:2 dilutions in duplicate using an Aushon 2470 Arrayer. Each array has a total of 6912 dots printed. Slides were probed with 150 antibodies (ABs) against predominantly apoptosis, cell cycle and STP regulating proteins including 105 vs. total protein, 40 vs. phos-specific sites and 5 vs. cleavage sites. Spot intensities were quantified using MicroVigene software. Data was analysed using R, with loading control and topographical background normalization being utilized. The sample set was randomly divided into a test (n=256) and validation (n=255) set. Correlation between this array and our prior array, which shared 189 samples and 49 AB, was outstanding with 43/49 AB showing Pearson and Spearman correlations with P <0.0001, demonstrating reproducibility. Expression in PB and BM were similar for all but 18 proteins. Samples prepared from cryopreserved specimens had similar expression compared to those prepared from fresh cells. Expression of 53 proteins distinguished FAB subtypes. Different ProExpSig were observed for recurrent cytogenetic abnormalities as well, with unfavorable cytogenetics -5, -7 and -5,-7 having similar signatures, suggesting that common downstream effects can arise from different chromosomal abnormalities. ProExpSig for complete remission (CR) vs. resistance (RES) were defined with 17 proteins showing significantly higher expression among CR cases and 20 being higher among RES cases. Likewise ProExpSig that predicted for REL vs. continuous CR (CCR) were defined with 6 proteins showing significantly higher expression among CCR cases and 5 being higher among REL cases. ProExpSig for event free survival, based on 20 proteins, 12 significantly higher levels and 8 significantly lower in survivors, predicted outcome. Principle component analysis was performed and defined 12 constellations of proteins with correlated expression. The combined pattern from each constellation was utilized to divide patients into 8 ProExpSig. Some showed correlation with cytogenetics but provided independent prognostic information within cytogenetic groupings (favorable, intermediate, and unfavorable). After finalization of the test set analysis the generated hypotheses will be tested against the validation set. In summary we confirm the that ProExpSig exist in AML and are prognostic. Since these ProExpSig are based on different patterns of expression and activation of proteins that are being targeted by developmental agents this information may be utilized to direct patients toward optimal selection of targeted therapy and thereby contribute to personalized medicine.

Derepression in the Desert: The Third Workshop on Clinical Translation of Epigenetics in Cancer Therapeutics

In the past decade, the scientific and medical community has witnessed dramatic progress in epigenetics and has begun to understand some of the epigenetic mechanisms that contribute to human disease, particularly cancer. In January 2007, the third biannual workshop on Clinical Translation of

Cytotoxic T-Lymphocyte Harnessing CML66 Can Kill Human Myeloid Leukemia Cells, In Vitro.

[Purpose & background] CML66 is a newly identified cancer-testis antigen by SEREX method in post-transplant CML patient who had a second remission by DLI for relapse. Thus CML66 is initially considered to be implicated in graft-versus-leukemia (GvL) effect against CML, while its' physiological function remains unknown. The identification by SEREX means its' immunogenicity to produce antibody, however the T-cell response specific for CML66, particularly its' ability to generate cytotoxic T-lymphocyte (CTL) against leukemia still remains to be verified. Thus we explored a CTL-epitope of CML66 to induce epitope-specific CTL which can kill human leukemia cells, because of the exploration of its' clinical applicability as an anticancer vaccine for the immunotherapy.[Methods] At first, we synthesized a variety of CML66-derived 9 aminoacid peptides (9 mer) that had computedly-predicted high binding affinity to HLA-A*2402 molecule. CD8+ T lymphocytes from an HLA-A*2402+healthy donor were co-cultured with autologous monocyte-derived mature dendritic cells (mDCs). CD8+T lymphocytes were repeatedly stimulated with peptide-loaded mDCs. Thereafter, the target epitope-specificity of growing cells was examined by a standard 51Cr-release assay. Additionally, the blocking tests by using anti-HLA class I and anti-class II monoclonal antibody (mo.ab.) were conducted to confirm its' HLA-A*2402-restricted fashion. Next, CML66 mRNA expression level of target cells including myeloid leukemia cell line cells and primary leukemia cells was examined by real-time semi-quantitative PCR (RQ-PCR). The relative expression level of CML66 mRNA was determined by comparative Ct method.[Result] We identified two CML66-derived 9 mer epitopes with high binding affinity to HLA-A*2402 measured by using HLA-A*2402 gene transfected T2 (T2-A24) cell. One of 2 epitopes, the epitope of CML66; aa70–78: WIQDSVYYI generated the epitope-specific CTL, in vitro, and those CTL exerted anti-leukemia activity against human myeloid leukemia cell line cells in an HLA-A*2402-restricted fashion, but not any cytotoxicity against normal cells. Furthermore, the HLA-A*2402 restriction was confirmed by blocking test by HLA-class I and II mo.ab. Next CML66 mRNA expression level was revealed high in myeloid leukemia cell line cells but low in normal cells, which were compared to that of K562 cell line cell. In primay leukemia cells, acute myelogenous leukemia(AML) cells and acute lymphoblastic leukemia(ALL) cells showed the high expression level of CML66 mRNA. Regarding to the FAB classification of AML, the expression level of CML66 mRNA tended to be higher in subsets ranging from M1 to M4, particularly M2 cells. Even by small number, it was of interest that the expression level of CML66 mRNA in primary chronic myelogenous leukemia (CML) cells was high in cells from blastic phase, but low in cells from chronic phase. This finding may suggest the correlation between CML66 and growth activity of tumor cells.[Conclusion] We identified the novel HLA-A*2402 restricted CTL-epitope derived from CML66; aa70–78: WIQDSVYYI, which may be a promising and secure target for immunotherapy against acute leukemias and aggressive CML.

High Throughput Proteomic Analysis of 559 Acute Myelogenous Leukemia (AML) Patient Samples on a Single Slide Using Reverse Phase Proteins Arrays (RPPA): Analysis of Signal Transduction Pathway (STP) and Apoptosis Regulating Proteins.

We have previously demonstrated that protein expression profiling assessing the activation state of apoptosis and STP proteins could be successfully performed in Acute Myelogenous Leukemia (AML) patient samples using reverse phase protein arrays (RPPA). With the goal of providing comprehensive proteomic based classification of AML we have now generated an array using protein derived from the leukemia enriched fraction of 559 primary AML samples. Included are 326 samples from 263 newly diagnosed AML patients (176 Marrow, 149 blood samples, 63 with concurrent blood and marrow specimens), 61 primary refractory, and 163 relapse specimens. Also present on the array are 120 purified peptides, 18 cell lines, 18 normal peripheral blood or bone marrow samples. All specimens are printed with 5 serial 1:3 dilutions in duplicate on geographically separate locations of the slide. As a control for printing and staining variations each pair of samples is flanked by a positive control cell line mixture and buffer only negative control. Each array has a total of 8064 dots printed using a Aushon 2470 Arrayer. 64 slides were produced and within 7 days probed with 54 validated antibodies against apoptosis and STP proteins, including 20 phos-specific antibodies (ABs), demonstrating the high throughput capability of the system. Seven duplicate slides were stained a week after the first staining to test reproducibility. Spot intensities were quantified using MicroVigene software. The positive and negative control printed across the slide were used to generate a topographical map of staining density across the slide. The negative control values are subtracted on a regional basis to provide background correction and the cell line positive control is utilized to normalize the range. The purified peptides permit protein quantification. The developed slides generally were of very high quality with all but 3 slides providing interpretable data. Intra- and inter- slide reproducibility was very high. The samples set was randomly divided into a test and validation set. Unsupervised hierarchical clustering analysis on the proteins is being performed using perturbation bootstrap resampling to assess the significance of clusters. Preliminary analysis suggests that several reproducible clusters exist, similar to our findings with the screening array (see Tibes et al., ASH 2005) and that these clusters correlate with remission attainment, relapse or overall survival. This dataset will undergo addition analysis after additional proteins are assayed to yield a more comprehensive proteomic based classification of AML. This sample set contains 123 patients on our cytokine array (see Kornblau et al., ASH 2006) permitting association between cytokine expression level and the activation status of the STP and apoptosis pathways. This array provides the ability to rapidly screen large numbers of AML patient samples for expression and activation state. Distinct pathway activation patterns can classify AML, provide prognostic guidance and may serve to triage patients to emerging targeted therapies aimed at these pathways.

Classification of Acute Myelogenous Leukemia (AML) Based on Patterns of Signal Transduction Pathway (STP) and Apoptosis Regulating Protein Activation Determined by Reverse Phase Proteins Arrays (RPPA).

We have previously shown that the protein expression profile and especially the activation state of apoptosis and STP proteins are highly prognostic in AML. The development of RPPA permits a more comprehensive analysis of protein expression and phosphorylation (phos) patterns in the STP and apoptotic cascades. We have generated a screening array using protein derived from the leukemia enriched fraction of 94 primary AML samples (with 21 concurrent blood and marrow specimens), comprised equally of patients that were primary refractory (PrimRef), or that achieved complete remission that was continuous (CCR) or which relapsed after 6 to 24 months (REL). These slides have been probed with 22 total and 15 phos-specific antibodies (ABs) against apoptosis and STP proteins. Spot intensities were quantified using MicroVigene and the data for each protein standardized data by subtracting the mean expression levels across samples and dividing by the standard deviation. Unsupervised hierarchical clustering analysis on the proteins was performed. We found one small cluster of 5 proteins: Cyclin D1, β-catenin, phos-NMP, p53, and AMPK. The remaining proteins formed another cluster, with a subset of 8 proteins somewhat further separated. In several cases (mTOR, JNK, and PTEN) the total protein amounts clustered as nearest neighbors to the phos version of the same protein. Using perturbation bootstrap resampling to assess the significance of clusters we found 4 reproducible clusters and the structure suggests additional clusters in this data set. A Fisher exact test showed that these were significantly associated with response (p = 0.03) and with the prognostic category defined by cytogenetics (p = 0.04) but was not associated with the source (blood vs. marrow) of the sample (p = 0.67). Ten proteins were differentially expressed between cytogenetically defined prognostic groups: total and phospho AKT, PTEN and JNK, p-mTOR, p-STAT3, pp38 and PS6.p24.44 (all with P<0.02). No protein was prognostic for response across the entire population but several were prognostic for response and survival within specific clusters. Clustering of ratios of phos-/total AB revealed 2 patterns: one with higher phos- of kinases (“kinase high”); another with low kinase expression (“kinase low”) but higher phos- of apoptosis regulating proteins. In the “kinase high” cluster single or concurrent increased activation of pAkt308, pAkt473, pPKCa, p-mTor (2448), pErk1,2 (42/44), p-p38 over their corresponding total protein was associated with worse outcome (~15% CCR rate). Those with increased Bcl2/Bax and pJNK/JNK levels fared worse with only 10% CCR. A favorable outcome was associated with concurrent high pAkt308/Akt and pGSK3/GSK3 levels (50% CCR) or being in the “kinase low” group while having high pStat3(705)/Stat3 levels (58% CCRs). The identified clusters and their correlation with cytogenetic group and outcome mainly driven by the activated, phospho protein forms, strongly supports the idea that the activation state of STP and apoptotic regulators determines biological behavior and clinical outcome. Distinct pathway activation patterns can classify AML, provide prognostic guidance and may serve to triage patients to emerging targeted therapies aimed at these pathways.

Overexpression of Cyclin E in Acute Myelogenous Leukemia

AbstractCyclin E is one of the G1 cyclins that play an important role in cell proliferation. Overexpression of cyclin E protein has been reported in several solid tumors, but little is known about the involvement of cyclin E in leukemia. In this study, we analyzed the expression of cyclin E gene product in 85 patients with acute myelogenous leukemia (AML) by Western blot analysis. In 23 of 85 AML samples (27%), cyclin E expression was enhanced in blasts. Among the French-American-British classification of AML, the ratio of the samples with enhanced cyclin E expression was high in M5 and low in M2 and M3. No rearrangements were observed by Southern blot analysis in these AML blasts with enhanced cyclin E expression. Flow cytometric analysis showed no correlation between overexpression of cyclin E and cell cycle distribution. Immunoblot analysis of cyclin D1 showed no correlation between overexpression of cyclin E and that of cyclin D1. Interestingly, p27 expression detected by Western blotting was apparently enhanced in 18 of 23 AML cells with enhanced cyclin E expression but none of 14 AML cells without enhanced cyclin E exhibited enhanced p27 expression. The rates of complete remission and of disease-free survival of the patients with M4 or M5 leukemia blasts with overexpressed cyclin E seemed to be low. Therefore, we suggest the necessity of a larger-scale study to elucidate the contribution of cyclin E overexpression to the phenotype and the prognosis of certain AML.

Aberrant Expression of CD19 as a Marker of Monocytic Lineage in Acute Myelogenous Leukemia

Immunophenotypic analysis plays a critical role in the diagnosis and classification of acute leukemia. Certain characteristic immunophenotypic patterns have emerged that aid in the classification of acute myelogenous leukemia (AML). We describe a unique pattern of expression of CD19, a B cell-associated cell surface antigen, in cases of AML. We reviewed 59 cases of de novo AML to determine the pattern of CD19 expression in cases of AML using three different CD19 monoclonal antibodies, including B4 (Lytic), B4 89B (Coulter, Miami, Fla) and SJ25-C1 (GenTrak, Plymouth Meeting, Pa). We confirmed the known relationship between CD19 expression and t(8;21)-positive AML M2; in these cases, CD19 was detected with all three antibodies. We also found a unique pattern of CD19 expression in cases of AML with a substantial monocytic-monoblastic component. In 6 of 12 cases of AML M4 or M5, CD19 expression was evident only with the B4 (Lytic) antibody; CD19 expression was not observed using B4 89B or SJ25-C1. We did not observe any recurring chromosomal abnormalities in these cases of CD19-positive AML M4/M5; furthermore, none of these cases demonstrated a t(8;21). Using CD11b, CD14, and other myeloid markers, we found that AML M4 and AML M5 were characterized by dual populations of blasts. With the exception of a case of AML M4 eo, cases of AML M4 were associated with one population of blasts lacking both CD11b and CD14 and a second population with one or both of these antigens. Cases of AML M5 also had dual populations of blasts, but in contrast with AML M4, each population expressed CD11b, CD14, or both. Our findings suggest that specific immunophenotypic patterns, including the unique pattern of CD19 expression with the B4 (Lytic) monoclonal antibody, may prove useful in classifying cases of AML M4 and M5.

Classification of AML by morphologic, immunologic and cytogenetic criteria. Review with reference to subtypes in the AML-BFM-87 study

The current FAB classification of acute myelogenous leukemia (AML) by morphologic, immunologic and cytogenetic features is described and the incidence of subtypes and variant forms of AML in study AML-BFM-87 is given. In general, lymphoblastic or myeloid blast populations can be identified by morphologic, cytochemical and immunologic parameters, while immunophenotyping facilitates diagnosis in biphenotypic leukemia. Furthermore, the AML subtypes M0 and M7 (defined in 1985 and 1991) can only be ascertained by the presence of lineage-associated markers. Whereas chromosome aberrations provide an insight into the neoplastic process and assure diagnosis. Thus, next to morphologic findings, immunologic and cytogenetic studies are essential for a definite diagnosis of AML.

Toward a clinically relevant cytogenetic classification of acute myelogenous leukemia

Cytogenetic studies with Giemsa banding were performed on the bone marrow cells of 384 patients with acute myelogenous leukemia treated between 1975 and 1983. An abnormal karyotype was detected in 54% of patients, being present in 100% of metaphases (AA) in 31% and only a proportion of cells (AN) in 22%. Specific translocations or other abnormalities were noted in 22% of patients, the most common of which were t(8;21) (q22;q22) in 7%, t(15;17) (q22;q21) and inv (16) (p13q22) in 5.5%, t(9;22) (q34;q11) in 3% and abnormalities of 11q23 in 1.3%. Loss of the Y chromosome was noted in 21 patients, associated with t(8;21) in 11 patients and the sole abnormality in eight patients (45, X, -Y). Most (66%) of the other abnormalities involved addition of chromosome 8 or loss or deletion of 5 or 7 (+8, -5 or -7, 5q- or 7q-group). The remaining patients had miscellaneous abnormalities (MA). A marked assymetry was noted in the distribution of important clinical prognostic variables such as age, sex, history of an antecedent hematologic disorder and presence of Auer rods within the various cytogenetic categories. The specific translocation/abnormalities were more common in younger patients ( p < 0.01). Analysis of response, remission duration and survival demonstrated that inv 16 and t(8;21) were favorable prognostic categories; diploid, t(15;17) and 45,X,-Y had intermediate prognosis, and all other categories were unfavorable prognostic groups. The response rate and survival for diploid patients (NN) was superior to patients with abnormalities. No difference in response rate, CR duration or survival was noted between the AA and AN groups. A prognostic classification according to cytogenetic category based on clinical associations is proposed which will be tested prospectively in subsequent studies.

Classifying acute leukemia by immunophenotyping: a combined FAB- immunologic classification of AML

A panel of commercially available monoclonal antibodies and five heteroantisera were used to distinguish and subtype 138 cases of acute leukemia (AL). The immunophenotype was compared with the French-American-British (FAB) classification obtained on the cases. The immunophenotype discriminated acute myelogenous leukemia (AML) from acute lymphoblastic leukemia (ALL) and recognized cases not distinguished by cytochemistry (22% of cases), mixed lineage phenotypes (13% of cases), and cases with separate populations of lymphoblasts and myeloblasts (one case). Using the immunologic panel and derived criteria to subtype AML, correspondence of the immunophenotype to the FAB subtypes M1, M2, M4, and M5 was possible in greater than 80% of cases. A combined classification of the immunophenotype and FAB morphology/cytochemistry was devised for AML subtyping. It is recommended that immunophenotyping should be done at least in all cases with negative or inconclusive cytochemistry. At present, we suggest that until a "gold standard" for identifying leukemic subtypes is developed, the best method for typing acute leukemia is by using a combination of morphology, cytochemistry and immunophenotyping.

Classifying Acute Leukemia by Immunophenotyping: A Combined FAB-Immunologic Classification of AML

Abstract A panel of commercially available monoclonal antibodies and five heteroantisera were used to distinguish and subtype 138 cases of acute leukemia (AL). The immunophenotype was compared with the French- American-British (FAB) classification obtained on the cases. The immunophenotype discriminated acute myelogenous leukemia (AML) from acute lymphoblastic leukemia (ALL) and recognized cases not distinguished by cytochemistry (22% of cases), mixed lineage phenotypes (13% of cases), and cases with separate populations of lymphoblasts and myeloblasts (one case). Using the immunologic panel and derived criteria to subtype AML, correspondence of the immunophenotype to the FAB subtypes M1, M2, M4, and M5 was possible in greater than 80% of cases. A combined classification of the immunophenotype and FAB morphology/cytochemistry was devised for AML subtyping. It is recommended that immunophenotyping should be done at least in all cases with negative orinconclusive cytochemistry. At present, we suggest that until a “gold standard” for identifying leukemic subtypes is developed, the best method for typing acute leukemia is by using a combination of morphology, cytochemistry and immunophenotyping.

Ultrastructural peroxidase cytochemistry of leukemic cells. I. Classification of acute myelogenous leukemia.

Twenty three cases of acute myelogenous leukemia (AML) were in-vestigated by ultrastructural peroxidase cytochemistry. The 23 cases were classified into two groups, Group A and B. In Group A (7 cases), the pre-dominant leukemic cells were without granules, while in Group B (16 cases), the predominant cells were with granules. Leukemic cells without granules showed peroxidase reaction product in the nuclear envelope and rough endo-plasmic reticulum (RER). These cells were identified as leukemic myeloblasts. Leukemic cells with granules were recognized as leukemic promyelocytes by the presence of peroxidase reaction product in the nuclear envelope, RER, Golgi apparatus and all cytoplasmic granules. There was no significant difference in the granule size of leukemic promyelocytes between Group A and B (150-400 nm: the smallest diameter in a thin section). The leukemic promyelocyte of Group A, however, exhibited a higher nucleo-cytoplasmic ratio and a fewer number of granules than those of Group B, indicating that the leukemic pro-myelocyte of Group A was at an earlier stage of granule formation.These findings suggest that the predominant cells in Group A are of an immature type and those in Group B of a mature type. Clinically, the patients in Group A had a higher incidence of complete remission and a longer median survival time than those belonging to Group B.