RAMRSGL: A Robust Adaptive Multinomial Regression Model for Multicancer Classification

In view of the challenges of the group Lasso penalty methods for multicancer microarray data analysis, e.g., dividing genes into groups in advance and biological interpretability, we propose a robust adaptive multinomial regression with sparse group Lasso penalty (RAMRSGL) model. By adopting the overlapping clustering strategy, affinity propagation clustering is employed to obtain each cancer gene subtype, which explores the group structure of each cancer subtype and merges the groups of all subtypes. In addition, the data-driven weights based on noise are added to the sparse group Lasso penalty, combining with the multinomial log-likelihood function to perform multiclassification and adaptive group gene selection simultaneously. The experimental results on acute leukemia data verify the effectiveness of the proposed method.

Introduction and Classification of Leukemias

Classifying the hematological malignancies by assigning cells to their normal counterpart and describing the nature of disease progression are entirely reliant on an accurate picture for the development of the multifarious types of blood and immune cells. In recent years, our understanding of the complex relationships between the various hematopoietic stem cell-derived cell lineages has undergone substantial revision. There has been similar progress in how we describe the nature of the "target" cells that genetic insults transform to give rise to the hematological malignancies. Here I describe how both longstanding and new information has influenced classifying, for diagnosis, the hematological malignancies.

Myeloid/lymphoid neoplasms with eosinophilia and FLT3 rearrangement

Myeloid/lymphoid neoplasms with eosinophilia and gene rearrangement are a unique category in the WHO classification, and include cases with rearrangement of PDGFRA, PDGFRB, FGFR1, and PCM1-JAK2. We report three patients presented with eosinophilia and FLT3 rearrangement: the first case with chronic eosinophilic leukemia, not otherwise specified and T-lymphoblastic leukemia/lymphoma; the second case with myeloid sarcoma; and the last case with high-grade myelodysplastic syndrome. The first case showed t(13;14)(q12;q32), which encoded FLT3-TRIP11. The patient was treated with intense chemotherapy and subsequently sorafenib with clinical improvement. Unfortunately, the patient showed persistent residual disease and passed away 9 months after the diagnosis from pneumonia. The other two cases both showed ETV6-FLT3. The second patient was treated with local radiation and systemic chemotherapy including sorafenib and was alive. The third patient was treated with chemotherapy but showed transformation to acute myeloid leukemia and died 15 months after diagnosis. These cases are among a growing number of cases with FLT3 rearrangement that all showed similar clinicopathologic features characterized by myeloproliferative neoplasm with eosinophilia and frequent T lymphoblastic leukemia/lymphoma. Therefore, we propose that the myeloid/lymphoid neoplasms with eosinophilia and FLT3 rearrangement be included in the WHO category of myeloid/lymphoid neoplasms with eosinophilia and gene rearrangement.

DNA methylation markers in the diagnosis and prognosis of common leukemias

The ability to identify a specific type of leukemia using minimally invasive biopsies holds great promise to improve the diagnosis, treatment selection, and prognosis prediction of patients. Using genome-wide methylation profiling and machine learning methods, we investigated the utility of CpG methylation status to differentiate blood from patients with acute lymphocytic leukemia (ALL) or acute myelogenous leukemia (AML) from normal blood. We established a CpG methylation panel that can distinguish ALL and AML blood from normal blood as well as ALL blood from AML blood with high sensitivity and specificity. We then developed a methylation-based survival classifier with 23 CpGs for ALL and 20 CpGs for AML that could successfully divide patients into high-risk and low-risk groups, with significant differences in clinical outcome in each leukemia type. Together, these findings demonstrate that methylation profiles can be highly sensitive and specific in the accurate diagnosis of ALL and AML, with implications for the prediction of prognosis and treatment selection.

The Diagnostic Work-Up of Hypereosinophilia

Hypereosinophilia (HE) is defined as a persistent elevated eosinophil count of ≥1.5 × 109/L. HE can be one of the dominant manifestations of a hematopoietic myeloid neoplasm or secondary/reactive to an underlying medical condition. If a cause of HE and its associated tissue/organ damage is not determined, the condition is considered to be idiopathic hypereosinophilic syndrome (HES). The work-up of HE can be challenging due to a broad range of causes of HE that can be either reactive or neoplastic. In recent years, with the advent of molecular genetic testing and the introduction of targeted therapy in the management of these patients, there is a growing interest in better characterization of these diseases. Using a multimodality approach and following a proper -algorithm, a diagnosis can be made in a large proportion of patients. In idiopathic HES, myeloid neoplasm associated -somatic mutations as evidence of clonality are reported in -20-25% patients; however, the mutation data should be -interpreted cautiously considering the prevalence of clonal hematopoiesis of indeterminate potential (CHIP). Bone marrow morphology has been shown to have important value in the identification of a true myeloid neoplasm in these disorders. A genome-wide study may be needed to understand the "idiopathic" cases that would ultimately lead to better patient care.

Adult leukemia survival trends in the United States by subtype: A population-based registry study of 370,994 patients diagnosed during 1995-2009

BACKGROUND

The lifetime risk of developing leukemia in the United States is 1.5%. There are challenges in the estimation of population-based survival using registry data because treatments and prognosis vary greatly by subtype. The objective of the current study was to determine leukemia survival estimates in the United States from 1995 to 2009 according to subtype, sex, geographical area, and race.

METHODS

Five-year net survival was estimated using data for 370,994 patients from 43 registries in 37 states and in 6 metropolitan areas, covering approximately 81% of the adult (15-99 years) US population. Leukemia was categorized according to principal subtype (chronic lymphocytic leukemia, acute myeloid leukemia, and acute lymphocytic leukemia), and subcategorized in accordance with the HAEMACARE protocol. We analyzed age-standardized 5-year net survival by calendar period (1995-1999, 2000-2004, and 2005-2009), leukemia subtype, sex, race, and US state.

RESULTS

The age-standardized 5-year net survival estimates increased from 45.0% for patients diagnosed during 1995-1999 to 49.0% for those diagnosed during 2000-2004 and 52.0% for those diagnosed during 2005-2009. For patients diagnosed during 2005-2009, 5-year survival was 18.2% (95% confidence interval [95% CI], 17.8%-18.6%) for acute myeloid leukemia, 44.0% (95% CI, 43.2%-44.8%) for acute lymphocytic leukemia, and 77.3% (95% CI, 76.9%-77.7%) for chronic lymphocytic leukemia. For nearly all leukemia subtypes, survival declined in successive age groups above 45 to 54 years. Men were found to have slightly lower survival than women; however, this discrepancy was noted to have fallen in successive calendar periods. Net survival was substantially higher in white than black patients in all calendar periods. There were large differences in survival noted between states and metropolitan areas.

CONCLUSIONS

Survival from leukemia in US adults improved during 1995-2009. Some geographical differences in survival may be related to access to care. We found disparities in survival by sex and between black and white patients.

A gene signature that distinguishes conventional and leukemic nonnodal mantle cell lymphoma helps predict outcome

Mantle cell lymphoma (MCL) is an aggressive B-cell malignancy, but some patients have a very indolent evolution. This heterogeneous course is related, in part, to the different biological characteristics of conventional MCL (cMCL) and the distinct subgroup of leukemic nonnodal MCL (nnMCL). Robust criteria to distinguish these MCL subtypes and additional biological parameters that influence their evolution are not well defined. We describe a novel molecular assay that reliably distinguishes cMCL and nnMCL using blood samples. We trained a 16-gene assay (L-MCL16 assay) on the NanoString platform using 19 purified leukemic samples. The locked assay was applied to an independent cohort of 70 MCL patients with leukemic presentation. The assay assigned 37% of cases to nnMCL and 56% to cMCL. nnMCL and cMCL differed in nodal presentation, lactate dehydrogenase, immunoglobulin heavy chain gene mutational status, management options, genomic complexity, and CDKN2A/ATM deletions, but the proportion with 17p/TP53 aberrations was similar in both subgroups. Sequential samples showed that assay prediction was stable over time. nnMCL had a better overall survival (OS) than cMCL (3-year OS 92% vs 69%; P = .006) from the time of diagnosis and longer time to first treatment. Genomic complexity and TP53/CDKN2A aberrations predicted for shorter OS in the entire series and cMCL, whereas only genomic complexity was associated with shorter time to first treatment and OS in nnMCL. In conclusion, the newly developed assay robustly recognizes the 2 molecular subtypes of MCL in leukemic samples. Its combination with genetic alterations improves the prognostic evaluation and may provide useful biological information for management decisions.

A review of the automated detection and classification of acute leukaemia: Coherent taxonomy, datasets, validation and performance measurements, motivation, open challenges and recommendations

CONTEXT

Acute leukaemia diagnosis is a field requiring automated solutions, tools and methods and the ability to facilitate early detection and even prediction. Many studies have focused on the automatic detection and classification of acute leukaemia and their subtypes to promote enable highly accurate diagnosis.

OBJECTIVE

This study aimed to review and analyse literature related to the detection and classification of acute leukaemia. The factors that were considered to improve understanding on the field's various contextual aspects in published studies and characteristics were motivation, open challenges that confronted researchers and recommendations presented to researchers to enhance this vital research area.

METHODS

We systematically searched all articles about the classification and detection of acute leukaemia, as well as their evaluation and benchmarking, in three main databases: ScienceDirect, Web of Science and IEEE Xplore from 2007 to 2017. These indices were considered to be sufficiently extensive to encompass our field of literature.

RESULTS

Based on our inclusion and exclusion criteria, 89 articles were selected. Most studies (58/89) focused on the methods or algorithms of acute leukaemia classification, a number of papers (22/89) covered the developed systems for the detection or diagnosis of acute leukaemia and few papers (5/89) presented evaluation and comparative studies. The smallest portion (4/89) of articles comprised reviews and surveys.

DISCUSSION

Acute leukaemia diagnosis, which is a field requiring automated solutions, tools and methods, entails the ability to facilitate early detection or even prediction. Many studies have been performed on the automatic detection and classification of acute leukaemia and their subtypes to promote accurate diagnosis.

CONCLUSIONS

Research areas on medical-image classification vary, but they are all equally vital. We expect this systematic review to help emphasise current research opportunities and thus extend and create additional research fields.

Tumor Markers in Leukemia: Evaluation of Serum Levels of Different Forms of Sialic Acid, Regan Isoenzyme and Lactate Dehydrogenase

A sensitive and specific serum marker can greatly help in the early diagnosis of malignancy as well as in monitoring the treatment of cancer patients. The present work was initiated for determining serum levels of Total Sialic Acid (TSA), Lipid Bound Sialic Acid (LSA), Free Sialic Acid (FSA), Regan Isoenzyme (RI) and Lactate Dehydrogenase (LDH), so as to evaluate their value as potential tumor markers. Fifty patients with anemia and 78 patients with leukemia were studied. The leukemia group consisted of 32 cases of Acute Myeloid Leukemia (AML), 29 cases of Chronic Myeloid Leukemia (CML) and 17 cases of Acute Lymphatic Leukemia (ALL). The levels were compared with the values obtained from 88 healthy individuals. Compared to the healthy controls, all the biomarkers were significantly elevated in patients with anemia as well as in those with leukemia. However, in leukemia patients significantly higher levels of TSA, LSA, FSA and LDH were observed compared to anemia patients. TSA levels were significantly higher in AML patients compared to CML and ALL patients. LSA levels were also significantly higher in AML patients compared to ALL patients. LSA was the most sensitive (84.6%) while FSA and RI levels were the most specific (78.0%) markers for leukemia. The combined use of the markers showed increased sensitivity and specificity (100.0% and 98.0%, respectively). The study suggested that the biomarkers investigated might be used for differentiating anemic from leukemic conditions, however, more in-depth studies are indicated to assess their utility in classifying various leukemias.

Flow Cytometry in Pediatric Malignancies

The utility of flow cytometry as a useful diagnostic modality for the assessment of hematopoietic neoplasms has been established beyond doubt. In fact, it is now an integral part of the diagnosis and classification of various diseases like leukemias and lymphomas along with molecular studies and cytogenetics. Prognostication and disease monitoring by flow cytometry is also being recognized increasingly as one of the important fortes. This is evident by the number of articles in the published in literature on the minimal residual disease detection by flow cytometry especially in the last decade or so. To add to this, ever growing list of utilities in hematopoietic malignancies, many non-hematopoietic neoplasms can also be analyzed by flow cytometry. The examples include fluid specimens from serous cavity effusions and samples from solid tissues like lymph nodes, reticulo-endothelial tissue, central nervous system tissue, etc. Flow cytometry technique provides a unique blend of rapidity, high sensitivity and specificity compared to cyto-morphology and conventional immunohistochemical staining. It is also remarkable for simultaneous analysis of more than one marker on the cells. Evaluation of limited samples such as cerebrospinal fluid or fine needle aspiration samples makes Flow cytometry a valuable tool. DNA ploidy analysis and assessment of pediatric non-hematopoietic neoplasms by Flow cytometry has envisaged the utility vista of this technique. This review is aimed at providing an insight into the applications of flow cytometry in pediatric malignancies.

Recent perspectives of pediatric leukemia - an update

Leukemia is defined as an aberrant hyper-proliferation of immature blood cells that do not form solid tumor masses (i.e., liquid cancer). Usually, leukemia could be either of the myeloid or lymphoid lineages, and is classified as acute or chronic in nature. Chronic leukemias tend to have more mature cells and are rare in pediatric patients. Acute leukemias, on the other hand, are typically less mature and commonly occur in patients of all ages and are potentially rapidly fatal if not readily treated. The acute lymphoblastic leukemia (ALL) is the most common childhood malignancy. Similar to AML, and in some cases, on the same disease spectrum, are the myelodysplastic syndromes (MDS). The present review is focused on the recent perspectives of pediatric leukemia.

[Mediastinal germ cell tumors]

The mediastinum is among the most frequent anatomic region in which germ cell tumors (GCT) arise, second only to the gonads. Mediastinal GCT (mGCT) account for 16 % of all mediastinal neoplasms. Although the morphology and (according to all available data) the molecular genetics of mediastinal and gonadal GCT are identical, a number of unique aspects exist. There is a highly relevant bi-modal age distribution. In pre-pubertal children of both sexes, mGCT consist exclusively of teratomas and yolk sac tumors. The prognosis is generally favorable with modern treatment. In post-pubertal adults, virtually all patients with malignant mGCT are males; the prognosis is more guarded and depends (among other factors) on the histological GCT components and is similar to GCT in other organs. So-called somatic type malignancies (i. e. clonally related, non-germ cell neoplasias arising in a GCT) are much more frequent in mGCT than in other organs, and the association between mediastinal yolk sac tumors and hematological malignancies, such as myelodysplasias and leukemias, is unique to mediastinal tumors. The prognosis of GCT with somatic type malignancies is generally dismal.

Clinical presentations of acute leukemia

OBJECTIVE

To document the clinical presentation and epidemiology of various types of acute leukemia with their respective referral source at a tertiary level centre in Peshawar.

STUDY DESIGN

An observational study.

PLACE AND DURATION OF STUDY

Department of Pathology, Hayatabad Medical Complex (HMC), Peshawar, from January 2011 to May 2012.

METHODOLOGY

A total of 618 bone marrow biopsy reports were reviewed. All biopsy reports labeled as acute leukemia were reviewed for age, gender, address, referring unit, diagnosis on bone marrow examination, presenting complaints, duration of illness and findings of clinical examination.

RESULTS

Ninety-two patients were diagnosed as suffering from acute leukemias (15%). ALL was most prevalent (46%), followed by AML (38%) and undifferentiated acute leukemia (16%). Males were affected more compared to females (60% vs. 40%). ALL and AML were predominant in pediatric (64%) and adults (77%) patients respectively. Patients from Afghanistan accounted for 33% of all cases followed by Peshawar (14%). Fever (77%), pallor (33%) and bleeding disorders (23%) were the main presenting complaints. Enlargement of liver, spleen and lymph nodes together was associated with ALL compared with AML (p = 0.004).

CONCLUSION

ALL-L1 and AML-M4 were the most common sub-types. Fever, pallor and bleeding disorders were the main presenting complaints. Enlargement of liver, spleen and lymph nodes was more frequently associated with ALL compared to AML.

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a semi-supervised projective non-negative matrix factorization method (Semi-PNMF) to learn an effective classifier from both labeled and unlabeled samples, thus boosting subsequent cancer classification performance. In particular, Semi-PNMF jointly learns a non-negative subspace from concatenated labeled and unlabeled samples and indicates classes by the positions of the maximum entries of their coefficients. Because Semi-PNMF incorporates statistical information from the large volume of unlabeled samples in the learned subspace, it can learn more representative subspaces and boost classification performance. We developed a multiplicative update rule (MUR) to optimize Semi-PNMF and proved its convergence. The experimental results of cancer classification for two multiclass cancer gene expression profile datasets show that Semi-PNMF outperforms the representative methods.

Multiclass cancer classification based on gene expression comparison

As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analyses, microarray-based cancer classification comprising multiple discriminatory molecular markers is an emerging trend. Such multiclass classification problems pose new methodological and computational challenges for developing novel and effective statistical approaches. In this paper, we introduce a new approach for classifying multiple disease states associated with cancer based on gene expression profiles. Our method focuses on detecting small sets of genes in which the relative comparison of their expression values leads to class discrimination. For an m-class problem, the classification rule typically depends on a small number of m-gene sets, which provide transparent decision boundaries and allow for potential biological interpretations. We first test our approach on seven common gene expression datasets and compare it with popular classification methods including support vector machines and random forests. We then consider an extremely large cohort of leukemia cancer patients to further assess its effectiveness. In both experiments, our method yields comparable or even better results to benchmark classifiers. In addition, we demonstrate that our approach can integrate pathway analysis of gene expression to provide accurate and biological meaningful classification.

[What Has Been Done in Surugadai Nihon University Hospital as a Laboratory Physician--Encounter with FAB Classification and Establishing the Additional Laboratory Management Fee]

I was requested by Nihon University to contribute to the official journal of the Japanese Society of Laboratory Medicine (Rinsho Byori). A special review of the final lecture at Surugadai Nihon University Hospital was requested by the editorial board of the Japanese Society of Laboratory Medicine. I submitted a review under the heading of "I have carried out upon retirement, ..." based on the final lecture at Surugadai Nihon University Hospital. The contents of the lecture were how to widely disseminate the FAB classification of acute leukemia and how to establish an additional laboratory management fee. Finally, I showed how to charge an additional management fee correctly based on a laboratory physician's activities in Surugadai Nihon University Hospital. I summarize the lecture in this article.

The level of bone marrow WT1 message is a useful marker to differentiate myelodysplastic syndromes with low blast percentage from cytopenia due to other reasons

OBJECTIVE

Myelodysplastic syndromes (MDS) are a group of hematological neoplasms associated with ineffective hematopoiesis and that transform to acute leukemia. Distinguishing MDS from other cytopenias is sometimes difficult even for trained hematologists. WT1, the gene mutated in Wilms' tumor, was found expressed in acute myeloid leukemia and MDS. The amount of WT1 in peripheral blood and bone marrow (BM) is low in low-risk MDS subtypes, and is high in high-risk MDS subtypes. However, the role of WT1 in the differential diagnosis between MDS and other diseases showing cytopenia has not been fully addressed. The present study evaluated whether WT1 expression level can assist in the differential diagnosis of MDS from other cytopenias.

METHODS

The amount of WT1 message was evaluated among 56 MDS patients and 47 patients with cytopenia for various other reasons (cytopenia VR) at the Nagasaki University Hospital.

RESULTS

The level of WT1 was significantly related to the percentage of blasts in BM among MDS cases, and the type of French-American-British classification of MDS; refractory anemia (RA) cases showed significantly lower WT1 level than patients with RA with excess blasts. WT1 level was significantly related to the prognostic risk categories of MDS by the International Prognostic Scoring System (IPSS) and the revised IPSS. Although the blast percentage in the BM of RA and cytopenia VR were both less than 5%, there was a significant difference in the level of WT1 between MDS and cytopenia VR.

CONCLUSION

WT1 might be a good marker to differentiate low blast percentage MDS and cytopenia VR.

Textual Definitions in the Leukemia Domain: Methodological Guidelines for Biomedical Ontologies

The goal of our study is to establish methodological guidelines for the formulation of definitions in biomedical ontologies thatare not so common in the field of Library & Information Science.

Adoption of array technologies into the clinical laboratory

Array-based methods are making substantial contributions to the discovery of disease biomarkers and are fueling the growth of multianalyte testing for disease diagnosis and treatment. The distillation of high-density array results into sets of signature markers promises to improve disease staging, risk stratification and treatment decisions. To accommodate the growing requirement for multiplex testing, clinical laboratories are converting several single-analyte tests into array-based formats. However, adoption of array technologies provides several challenges to the laboratory, which must evaluate these new formats, train laboratory personnel, market the new services and obtain reimbursement for new analytes. Liquid-bead arrays are an attractive format for routine clinical diagnostics due to a combination of appropriate analyte density, simultaneous array decoding and detection, and flexibility for rapid customization. In this review, the suitability of several array platforms to diagnostic testing and applications of liquid-bead arrays for cystic fibrosis testing, multidisease carrier status assays and leukemia subtyping are discussed. As our understanding of the clinical utility of new or established biomarkers and recommendations for testing change, flexibility and adaptability of array platforms will be imperative. Future development of novel assay formats and improved quantitation will expand the number of diseases tested and lead to further integration into the diagnostic laboratory.

Use of gene expression microarrays for the study of acute leukemia

Genetic lesions found in acute leukemia drive the pathology of the disease in addition to forming reliable classifications of prognosis. However, there is still a reasonable heterogeneity of response among cases with the same genetic lesion. Moreover, many leukemia cases have no detectable genetic marker and these cases have marked heterogeneity of response. How can we learn more about the genes and pathways involved with leukemogenesis and response in the midst of such complexity? Gene expression microarrays are experimental platforms that allow for the simultaneous evaluation of the thousands of mRNA transcripts (the 'transcriptome'). This technology has revolutionized the study of leukemia, giving insight into genes and pathways involved in disease response and the biology involved in specific translocations.

Acute Leukemia Subclassification: A Marker Protein Expression Perspective

Improved leukemia classification and tailoring of therapy have greatly improved patient outcome particularly for children with acute leukemia (AL). Using immunophenotyping, molecular genetics and cytogenetics the low hanging fruits of biomedical research have been successfully incorporated in routine diagnosis of leukemia subclasses. Future improvements in the classification and understanding of leukemia biology will very likely be more slow and laborious. Recently, gene expression profiling has provided a framework for the global molecular analysis of hematological cancers, and high throughput proteomic analysis of leukemia samples is on the way. Here we consider classification of acute leukemia samples by flow cytometry using the marker proteins of immunophenotyping as a component of the proteome. Marker protein expressions are converted into quantitative expression values and subjected to computational analysis. Quantitative multivariate analysis from panels of marker proteins has demonstrated that marker protein expression profiles can distinguish MLLre from non-MLLre ALL cases and also allow to specifically distinguish MLL/AF4 cases. Potentially, these quantitative expression analyses can be used in clinical diagnosis. Immunophenotypic data collection using flow cytometry is a fast and relatively easily accessible technology that has already been implemented in most centers for leukemia diagnosis and the translation into quantitative expression data sets is a matter of flow cytometer settings and output calibration. However, before application in clinical diagnostics can occur it is crucial that quantitative immunophenotypic data set analysis is validated in independent experiments and in large data sets.

Multicategory reclassification statistics for assessing improvements in diagnostic accuracy

In this paper, we extend the definitions of the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) in the context of multicategory classification. Both measures were proposed in Pencina and others (2008. Evaluating the added predictive ability of a new marker: from area under the receiver operating characteristic (ROC) curve to reclassification and beyond. Statistics in Medicine 27, 157-172) as numeric characterizations of accuracy improvement for binary diagnostic tests and were shown to have certain advantage over analyses based on ROC curves or other regression approaches. Estimation and inference procedures for the multiclass NRI and IDI are provided in this paper along with necessary asymptotic distributional results. Simulations are conducted to study the finite-sample properties of the proposed estimators. Two medical examples are considered to illustrate our methodology.

MicroRNA profiling can classify acute leukemias of ambiguous lineage as either acute myeloid leukemia or acute lymphoid leukemia

PURPOSE

Classification of acute leukemia is based on the commitment of leukemic cells to the myeloid or the lymphoid lineage. However, a small percentage of acute leukemia cases lack straightforward immunophenotypical lineage commitment. These leukemias of ambiguous lineage represent a heterogeneous category of acute leukemia that cannot be classified as either acute myeloid leukemia (AML) or acute lymphoid leukemia (ALL). The lack of clear classification of acute leukemias of ambiguous lineage as either AML or ALL is a hurdle in treatment choice for these patients.

EXPERIMENTAL DESIGN

Here, we compared the microRNA (miRNA) expression profiles of 17 cases with acute leukemia of ambiguous lineage and 16 cases of AML, B-cell acute lymphoid leukemia (B-ALL), and T-cell acute lymphoid leukemia (T-ALL).

RESULTS

We show that leukemias of ambiguous lineage do not segregate as a separate entity but exhibit miRNA expression profiles similar to AML, B-ALL, or T-ALL. We show that by using only 5 of the most lineage-discriminative miRNAs, we are able to define acute leukemia of ambiguous lineage as either AML or ALL.

CONCLUSION

Our results indicate the presence of a myeloid or lymphoid lineage-specific genotype, as reflected by miRNA expression, in these acute leukemias despite their ambiguous immunophenotype. miRNA-based classification of acute leukemia of ambiguous lineage might be of additional value in therapeutic decision making.

Expression of small nucleolar RNAs in leukemic cells

PURPOSE

Small nucleolar RNAs (snoRNAs) direct sequence-specific modifications to ribosomal RNA. We hypothesized that the expression of snoRNAs may be altered in leukemic cells.

METHODS

The expression of snoRNAs was analyzed in various leukemic cell lines by massive parallel sequencing (SOLiD). Quantitative real-time PCR (RT-qPCR) was used to validate the expression profiles.

RESULTS

Our results show characteristic differences in the expression patterns of snoRNAs between cell lines representing the main subgroups of leukemia, AML, pre-B-ALL and T-ALL, respectively. In RT-qPCR analyses, several snoRNAs were found to be differentially expressed in T-ALL as compared to pre-B-ALL cell lines.

CONCLUSIONS

snoRNAs are differentially expressed in various leukemic cell lines and could, therefore, be potentially useful in the classification of leukemia subgroups.

Immunophenotypic characterization of acute leukemia at a public oncology reference center in Maranhão, northeastern Brazil

CONTEXT AND OBJECTIVES

The incidence of acute leukemia (AL) subtypes varies according to geographical distribution. The aim here was to determine the incidence of morphological and immunophenotypic AL subtypes in the state of Maranhão, Brazil, and to correlate the expression of aberrant phenotypes in children with acute lymphoblastic leukemia (ALL) with prognostic factors.

DESIGN AND SETTING

Single prospective cohort study at a public oncology reference center in Maranhão.

METHODS

Seventy AL cases were diagnosed between September 2008 and January 2010. For the diagnosis, complete blood cell counts, myelograms (at diagnosis and at the end of the induction phase), cytochemical analysis and immunophenotyping were performed.

RESULTS

Among adult patients (n = 22), the incidence of AL types was: ALL (22.7%) and acute myeloid leukemia (AML) (77.3%). The subtype AML M0 occurred most frequently (29.4%). In children (n = 48), the types were: AML (18.7%), most frequently subtype AML M4 (33.4%); biphenotypic acute leukemia (BAL) (4.2%); and ALL (77.1%), including the subtypes B-ALL (72.9%) and T-ALL (27.1%). Among the children with ALL, there were no statistically significant differences between patients with and without aberrant phenotypes, in relation to hematological parameters and treatment response.

CONCLUSION

This work demonstrates that the frequencies of AML M0 cases among adults and T-ALL cases among children in Maranhão were high. This suggests that there may be differences in AML subtype incidence, as seen with ALL subtypes, in different regions of Brazil. No association was found between the expression of aberrant phenotypes and prognostic factors, in children with ALL.

Survival of European patients diagnosed with lymphoid neoplasms in 2000-2002: results of the HAEMACARE project

BACKGROUND

The European Cancer Registry-based project on hematologic malignancies (HAEMACARE), set up to improve the availability and standardization of data on hematologic malignancies in Europe, used the European Cancer Registry-based project on survival and care of cancer patients (EUROCARE-4) database to produce a new grouping of hematologic neoplasms (defined by the International Classification of Diseases for Oncology, Third Edition and the 2001/2008 World Health Organization classifications) for epidemiological and public health purposes. We analyzed survival for lymphoid neoplasms in Europe by disease group, comparing survival between different European regions by age and sex.

DESIGN AND METHODS

Incident neoplasms recorded between 1995 to 2002 in 48 population-based cancer registries in 20 countries participating in EUROCARE-4 were analyzed. The period approach was used to estimate 5-year relative survival rates for patients diagnosed in 2000-2002, who did not have 5 years of follow up.

RESULTS

The 5-year relative survival rate was 57% overall but varied markedly between the defined groups. Variation in survival within the groups was relatively limited across European regions and less than in previous years. Survival differences between men and women were small. The relative survival for patients with all lymphoid neoplasms decreased substantially after the age of 50. The proportion of 'not otherwise specified' diagnoses increased with advancing age.

CONCLUSIONS

This is the first study to analyze survival of patients with lymphoid neoplasms, divided into groups characterized by similar epidemiological and clinical characteristics, providing a benchmark for more detailed analyses. This Europe-wide study suggests that previously noted differences in survival between regions have tended to decrease. The survival of patients with all neoplasms decreased markedly with age, while the proportion of 'not otherwise specified' diagnoses increased with advancing age. Thus the quality of diagnostic work-up and care decreased with age, suggesting that older patients may not be receiving optimal treatment.

Optimization based tumor classification from microarray gene expression data

BACKGROUND

An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE) for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types.

METHODOLOGY/PRINCIPAL FINDINGS

We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL), small round blue cell tumors (SRBCT) to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described.

CONCLUSIONS/SIGNIFICANCE

The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on different type of data sets, HBE method is an effective and consistent tool for cancer type prediction with a small number of gene markers.

Infusion of ex vivo expanded T regulatory cells in adults transplanted with umbilical cord blood: safety profile and detection kinetics

Acute graft-versus-host disease (aGVHD) is associated with high risk of morbidity and mortality and is a common complication after double umbilical cord blood (UCB) transplantation. To reduce these risks, we established a method of CD4(+)CD25(+)FoxP3(+) T regulatory cell (Treg) enrichment from cryopreserved UCB followed by a 18 (+) 1-day expansion culture including anti-CD3/anti-CD28 antibody-coated beads and recombinant human interleukin-2. In a "first-in-human" clinical trial, we evaluated the safety profile of UCB Treg in 23 patients. Patients received a dose of 0.1-30 × 10(5)UCB Treg/kg after double UCB transplantation. The targeted Treg dose was achieved in 74% of cultures, with all products being suppressive in vitro (median 86% suppression at a 1:4 ratio). No infusional toxicities were observed. After infusion, UCB Treg could be detected for 14 days, with the greatest proportion of circulating CD4(+)CD127(-)FoxP3(+) cells observed on day (+)2. Compared with identically treated 108 historical controls without Treg, there was a reduced incidence of grade II-IV aGVHD (43% vs 61%, P = .05) with no deleterious effect on risks of infection, relapse, or early mortality. These results set the stage for a definitive study of UCB Treg to determine its potency in preventing allogeneic aGVHD. This study is registered at http://www.clinicaltrials.gov as NCT00602693.

[Clinical and molecular biologic characteristics of 36 cases of leukemia with 11q23/mll]

This study was aimed to analyze the clinical and cytogenetic characteristics of acute leukemia with 11q23/mll rearrangement and explore the reasonable therapeutic principles. Characteristics in general situation, morphology, immunology, molecular biology, cytogenetics, treatment and overall survival of 36 cases of acute leukemias with mll gene rearrangement were studied and analyzed. The results showed that 36 cases with mll gene rearrangement were found positive (7.2%) in 494 patients with acute leukemia. Among the 36 cases of mll rearrangement positive, 32 cases were diagnosed as acute myeloid leukemia (AML) with myeloid antigen expression, of which 5 cases expressed lymphoblastic differentiation antigen; 4 cases were classified as B-lineage acute lymphoblastic leukemia (ALL), of which non-lineage myeloid expression pattern were found in 3 cases. In 29 out of 36 cases (80%) the clonal chromosomal aberration were detected, of which chromosome 11 aberration were observed in 22 cases. All patients received chemotherapy with a total response rate of 47.2%. Of the responded patients, 10 cases relapsed within 6 months, with a recurrence rate of 40%; 9 cases received hematopoietic stem cell transplantation (HSCT), 7 cases of which survived after transplantation. The median survival time of 36 cases was 16 months (range 2 - 46) and their 2-year overall survival rate was 41.4%. The 2-year overall survival rate of 9 patients who received HSCT was 87.5%. It is concluded that acute leukemia patients with mll gene rearrangement show poor response to chemotherapy, high recurrence rate and poor prognosis. Hematopoietic stem cell transplantation may be a reasonable treatment principle to improve these patients' survival situation.

Multimodal image analysis of chronic leukemic lymphoproliferative disorders and the hypothesis of "single" and "multiple" programmed stops in the development of typical and atypical forms of leukemias and lymphomas

The study consisted of morphometric analysis, assessment of the argyrophilic nucleolar organization region (AgNOR) characteristics, and image cytometry (ICM) in different tumor mass compartments: bone marrow (BM), peripheral blood (PB) and lymph nodes (LN) from patients with chronic leukemic lymphoproliferative disorders. A total of 71895 cells were analyzed on SFORM PC (VAMSTEC, Zagreb). Correlation between morphometric, AgNOR and ICM characteristics revealed the cells with low proliferative activity to possess small, homogeneous AgNOR, with the majority of cells in the peak of DNA histogram. The cells with high proliferative activity had inhomogeneous AgNOR, mostly containing greater DNA content than peak cells, pathologic mitoses (DNA > 4N), or the majority of cells were in the S-phase of the cell cycle. Cells with medium proliferative activity and annular AgNOR were in-between. Analysis of different tumor mass compartments showed that lymphatic cells with the affinity to accumulate in BM regularly exhibited low proliferative activity (a lower percentage of cells in SFC and highest percentage of cells in the peak of the G0/G1 phase). The cells in LN exhibited the characteristics of proliferative cells (an increased number of AgNOR, larger and more proliferative inhomogeneous AgNOR, and lowest percentage of cells in the G0/G1 phase). The migration of cells from BM to LN and between lymph nodes occurred through PB (there were cells with low and high proliferative activity: a higher proportion of cells in SFC and at the same time in the G0/G1 phase of the cell cycle). Analysis of cell size and proliferative activity in different compartments of tumor mass revealed that the cells in BM and PB did not differ substantially according to size and proliferative activity, while an inverse pattern was observed between PB and LN. As small cells are inactive and larger cells more proliferative, the analysis quite unexpectedly showed the PB cells to be largest and most inactive, in contrast to LN where the cells were smallest and most active. The "single" and "multiple programmed stops" have been hypothesized in the development of typical forms of leukemias and lymphomas and atypical forms of subacute and subchronic leukemias. Differentiation impairment may occur at any stage, and different "stop" locations result in different morphology and affinity to accumulation in bone marrow, peripheral blood and lymph nodes.

Mixed phenotype acute leukemia with t(11;19)(q23;p13.3)/ MLL-MLLT1(ENL), B/T-lymphoid type: A first case report

The majority of cases of acute leukemia belong to a specific lineage origin, either lymphoid or myeloid, and therefore are classified as acute lymphoblastic leukemia (ALL) or acute myelogenous leukemia (AML), based on morphologic features and cytochemical and immunophenotypic profile of the blast cells. A minority of acute leukemias however, show no clear evidence of differentiation along a single lineage. These are now classified under acute leukemias of ambiguous lineage by the most recent WHO classification and account for <4% of all cases of acute leukemia [1]. They include leukemias with no lineage specific antigens (acute undifferentiated leukemias) and those with blasts that express antigens of more than one lineage to such degree that it is not possible to assign the leukemia to any one particular lineage with certainty (mixed phenotype acute leukemias). The latter can either be leukemias with two distinct populations of blasts, each expressing antigens of a different lineage (historically referred to as "bilineal" leukemias) or a single blast population expressing antigens of multiple lineages (historically referred to as "biphenotypic" acute leukemias) [2]. Acute leukemias of ambiguous lineage may harbor a variety of genetic lesions. Those with t(9;22)(q34;q11) or translocations associated with mixed lineage leukemias (MLL) gene, i.e., t(11;V)(q23;V), occur frequently enough and are associated with distinct features, that are considered as separate entities according to the recent WHO classification. Co-expression of myeloid and B-lymphoid antigens is most common in mixed phenotype acute leukemia (MPAL), followed by co-expression of myeloid and T-lymphoid antigens, accounting for 66-70% and 23-24% of MLLs, respectively. Coexpression of B- and T-lineage associated antigens or antigens of all three lineages is exceedingly rare, accounting for <5% of MLLs [3,4]. The requirements for assigning more than one lineage to a single blast population has been established by current WHO classification [1].

Membrane proteomics for leukemia classification and drug target identification

Knowledge of protein expression in the plasma membrane of leukemia cells has contributed to improvements in the detection and treatment of hematological malignancies. Recently engineered antibodies against leukemia surface molecules have improved therapeutic efficacy compared with earlier agents, but there are still side effects. An increased understanding of the surface expression profiles and interactions of membrane proteins on leukemia cells will facilitate the expansion of the role of antibodies in therapy and enable the identification of novel biomarkers for the various stages of leukemogenesis and leukemia progression. Proteomic analysis enables the identification of thousands of proteins in a membrane extract and provides information on their relative abundance, interactions and post-translational modifications. Plasma membrane proteome analysis of leukemia cells can be used to define biomarkers for diagnosis, classification, prognosis and progression monitoring, as well as to predict therapeutic response or resistance. The effects of chemotherapy on the surface proteome and the functional consequences of perturbations to membrane protein networks can provide insights into leukemia cell signaling and survival mechanisms. Surface proteins that are differentially expressed on leukemia cells are prospective targets for the development of engineered antibodies or small-molecule therapeutics. This review focuses on recent discoveries in leukemia membrane proteomics and the potential for future research into leukemia classification and drug target identification.

Leukaemic Subtype of Marginal Zone Lymphoma: A Presentation of Three Cases and Literature Review

The recent World Health Organization (WHO) classification recognizes three subtypes of marginal zone lymphoma (MZL): extranodal MZL of mucosa-associated lymphoid tissue (MALT), splenic MZL and nodal MZL. As a group, MZL share morphological and immunophenotypic features similar to that of the marginal zone B-cell in secondary B-follicles, the postulated common cell of origin. There is, however, increasing information about molecular heterogeneity between the types of MZL, suggesting different aetiology and highlighting our current incomplete understanding of this evolving entity. We describe the presentation and clinical course of three patients with MZL who do not fit the currently recognized WHO categories, and best fit the putative category of MZL, leukaemic subtype. We review the current literature on this newly described entity, highlighting the importance of its recognition.

Incidence rates of the major leukemia subtypes among U.S. Hispanics, Blacks, and non-Hispanic Whites

While leukemia rates are thought to be lower in South and Central America, no study has systematically investigated incidence rates of the leukemia subtypes among Hispanics in the U.S. This was a retrospective cohort study, using data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute, 1992 - 2001, to compare leukemia incidence rates as a function of race and ethnicity. It was found that in adults, Hispanics had lower incidence rates for each of the major types of leukemia as compared to non-Hispanic Whites: For AML, elderly Whites had an incidence rate ratio (IRR) of 1.61 in comparison to Hispanics (p < 0.001) and 1.27 in comparison to Blacks (p < 0.001); for CML, the IRR among the elderly was 1.42 that of Hispanics (p < 0.001) and 1.22 that of Blacks (p = 0.003); and for CLL, the IRR was 2.31 times that of Hispanics (p < 0.001) and 1.48 times that of Blacks (p < 0.001). In ALL, however, Hispanics aged 0 - 19 had a significantly higher incidence rate than Whites and Blacks, with an IRR of 1.32 compared to Whites (p < 0.001), and 2.62 compared to Blacks (p < 0.001). In AML, CML, and CLL, among people age 65 or older, white non-Hispanics have higher incidence rates than Blacks, and Blacks have higher incidence rates than Hispanics. Childhood ALL incidence rates are highest among Hispanics, and lowest among Blacks.

Optimal aggregation of binary classifiers for multiclass cancer diagnosis using gene expression profiles

Multiclass classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. There have been many studies of aggregating binary classifiers to construct a multiclass classifier based on one-versus-the-rest (1R), one-versus-one (11), or other coding strategies, as well as some comparison studies between them. However, the studies found that the best coding depends on each situation. Therefore, a new problem, which we call the "optimal coding problem," has arisen: how can we determine which coding is the optimal one in each situation? To approach this optimal coding problem, we propose a novel framework for constructing a multiclass classifier, in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. Although there is no a priori answer to the optimal coding problem, our weight tuning method can be a consistent answer to the problem. We apply this method to various classification problems including a synthesized data set and some cancer diagnosis data sets from gene expression profiling. The results demonstrate that, in most situations, our method can improve classification accuracy over simple voting heuristics and is better than or comparable to state-of-the-art multiclass predictors.

[Demographic characteristics of patients with leukemia waiting for stem cell transplantation in Chinese Marrow Donor Program during 2000 to 2006]

OBJECTIVE

To explore the distributive characteristics for leukemia and to provide scientific reference for its prevention and intervention.

METHODS

Microsoft SQL 2005 databases was used to make a mathematical analysis of 3708 patients with leukemia in Chinese Marrow Donor Program (CMDP) from 2000 to 2006. The distributive characteristics were calculated by sex, age and area of patients with leukemia and then compared by constituent ratio and relative ratio statistics method.

RESULTS

A total of 3708 cases of leukemia were registered for waiting donor during the period 2000-2006 in CMDP, the age of patients were from 7 months to 69 years, the median age of diagnosis was 24.5 years, standard deviation was 6.7-years-old; males suffered more than females, and the ratio was 1.95: 1 (2451/1257). There were 1202 patients with acute lymphoblastic leukemia (ALL), 1066 with acute myeloid leukemia (AML), 1435 with chronic myeloid leukemia (CML), 5 with chronic lymphoblastic leukemia (CLL), CML was the most common patients. The distributive of 3708 patients with leukemia peak was from 15 to 30 years age group, 542 patients were at the age of 15 years, 559 patients were at the age group above 20 years, 514 patients were at the age above 25, 522 patients were at the age over 30-years-old. ALL patients were accounted for 49.36% (613/1242), AML patients accounted for 27.78% (245/1242), CML patients accounted for 22.78% (283/1242), CLL patients accounted for 0.08% (1/1242) in the age group of under 20 years (childhood group). All subjects were mainly in childhood patients with leukemia; The distributive of patients with leukemia in 30 areas were different, leukemia patients were not registered in one area, 494 patients were at the highest peak, 101 patients were in the median.

CONCLUSION

The majority of leukemia patients for waiting stem cell transplantation were registered among children and the adolescents groups, males were suffered more than the females. For children, the major type of leukemia was ALL, being necessary to pay more attention to the education of health, and the precaution of leukemia. The distributive of patients with leukemia for waiting stem cell transplantation was different in 30 areas, and the peak region of leukemia should be in Jiangsu, Guangdong, Shangdong, and Zhejiang provinces.

The Epidemiology of Childhood Leukemia with a Focus on Birth Weight and Diet

Leukemia is the most common childhood cancer and a major source of morbidity and mortality. The etiology of childhood leukemia remains largely unknown. Cytogenetic abnormalities determine disease subtypes, prognosis, clinical presentation, and course and may help in discovering etiological factors. Epidemiologic investigations of leukemia are complicated by many factors, including the rarity of the disease, necessitating careful study design. Two emerging areas of interest in leukemia etiology are birth weight and diet. High birth weight has been associated with increased risk of childhood leukemia. The biological mechanism behind this association may involve insulin-like growth factor I (IGF-I), which is associated with high birth weight. IGF-I may act by increasing the absolute number of stem cells available for transformation, stimulating the growth of cells that are already transformed, or a combination of effects. Diet has been linked with leukemia. Maternal dietary DNA topoisomerase II (DNAt2) inhibitor intake is associated with infant acute myeloid leukemia (AML) with the MLL gene translocation. Increased intake of fruits and vegetables has been associated with decreased leukemia risk and, relatedly, lack of maternal folate supplementation has been associated with increased childhood leukemia risk, possibly by causing DNA hypomethylation and increased DNA strand breaks. Methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms modify this risk.

Identifying differentially expressed genes in human acute leukemia and mouse brain microarray datasets utilizing QTModel

One of the essential issues in microarray data analysis is to identify differentially expressed genes (DEGs) under different experimental treatments. In this article, a statistical procedure was proposed to identify the DEGs for gene expression data with or without missing observations from microarray experiment with one- or two-treatment factors. An F statistic based on Henderson method III was constructed to test the significance of differential expression for each gene under different treatment(s) levels. The cutoff P value was adjusted to control the experimental-wise false discovery rate. A human acute leukemia dataset corrected from 38 leukemia patients was reanalyzed by the proposed method. In comparison to the results from significant analysis of microarray (SAM) and microarray analysis of variance (MAANOVA), it was indicated that the proposed method has similar performance with MAANOVA for data with one-treatment factor, but MAANOVA cannot directly handle missing data. In addition, a mouse brain dataset collected from six brain regions of two inbred strains (two-treatment factors) was reanalyzed to identify genes with distinct regional-specific expression patterns. The results showed that the proposed method could identify more distinct regional-specific expression patterns than the previous analysis of the same dataset. Moreover, a computer program was developed and incorporated in the software QTModel, which is freely available at http://ibi.zju.edu.cn/software/qtmodel .