Automatic B cell lymphoma detection using flow cytometry data

Background: Flow cytometry has been widely used for the diagnosis of various hematopoietic diseases. Although there have been advances in the number of biomarkers that can be analyzed simultaneously and technologies that enable fast performance, the diagnostic data are still interpreted by a manual gating strategy. The process is labor-intensive, time-consuming, and subject to human error. Results: We used 80 sets of flow cytometry data from 44 healthy donors, 21 patients with chronic lymphocytic leukemia (CLL), and 15 patients with follicular lymphoma (FL). Approximately 15% of data from each group were used to build the profiles. Our approach was able to successfully identify 36/37 healthy donor cases, 18/18 CLL cases, and 12/13 FL cases. Conclusions: This proof-of-concept study demonstrated that an automated diagnosis of CLL and FL can be obtained by examining the cell capture rates of a test case using the computational method based on the multi-profile detection algorithm. The testing phase of our system is efficient and can facilitate diagnosis of B-lymphocyte neoplasms

The tax-inducible actin-bundling protein fascin is crucial for release and cell-to-cell transmission of human T-cell leukemia virus type 1 (HTLV-1)

The delta-retrovirus Human T-cell leukemia virus type 1 (HTLV-1) preferentially infects CD4(+) T-cells via cell-to-cell transmission. Viruses are transmitted by polarized budding and by transfer of viral biofilms at the virological synapse (VS). Formation of the VS requires the viral Tax protein and polarization of the host cytoskeleton, however, molecular mechanisms of HTLV-1 cell-to-cell transmission remain incompletely understood. Recently, we could show Tax-dependent upregulation of the actin-bundling protein Fascin (FSCN-1) in HTLV-1-infected T-cells. Here, we report that Fascin contributes to HTLV-1 transmission. Using single-cycle replication-dependent HTLV-1 reporter vectors, we found that repression of endogenous Fascin by short hairpin RNAs and by Fascin-specific nanobodies impaired gag p19 release and cell-to-cell transmission in 293T cells. In Jurkat T-cells, Tax-induced Fascin expression enhanced virus release and Fascin-dependently augmented cell-to-cell transmission to Raji/CD4(+) B-cells. Repression of Fascin in HTLV-1-infected T-cells diminished virus release and gag p19 transfer to co-cultured T-cells. Spotting the mechanism, flow cytometry and automatic image analysis showed that Tax-induced T-cell conjugate formation occurred Fascin-independently. However, adhesion of HTLV-1-infected MT-2 cells in co-culture with Jurkat T-cells was reduced upon knockdown of Fascin, suggesting that Fascin contributes to dissemination of infected T-cells. Imaging of chronically infected MS9 T-cells in co-culture with Jurkat T-cells revealed that Fascin's localization at tight cell-cell contacts is accompanied by gag polarization suggesting that Fascin directly affects the distribution of gag to budding sites, and therefore, indirectly viral transmission. In detail, we found gag clusters that are interspersed with Fascin clusters, suggesting that Fascin makes room for gag in viral biofilms. Moreover, we observed short, Fascin-containing membrane extensions surrounding gag clusters and clutching uninfected T-cells. Finally, we detected Fascin and gag in long-distance cellular protrusions. Taken together, we show for the first time that HTLV-1 usurps the host cell factor Fascin to foster virus release and cell-to-cell transmission

Automatic Population of Structured Reports from Narrative Pathology Reports

There are a number of advantages for the use of structured pathology reports: they can ensure the accuracy and completeness of pathology reporting; it is easier for the referring doctors to glean pertinent information from them. The goal of this thesis is to extract pertinent information from free-text pathology reports and automatically populate structured reports for cancer diseases and identify the commonalities and differences in processing principles to obtain maximum accuracy. Three pathology corpora were annotated with entities and relationships between the entities in this study, namely the melanoma corpus, the colorectal cancer corpus and the lymphoma corpus. A supervised machine-learning based-approach, utilising conditional random fields learners, was developed to recognise medical entities from the corpora. By feature engineering, the best feature configurations were attained, which boosted the F-scores significantly from 4.2% to 6.8% on the training sets. Without proper negation and uncertainty detection, the quality of the structured reports will be diminished. The negation and uncertainty detection modules were built to handle this problem. The modules obtained overall F-scores ranging from 76.6% to 91.0% on the test sets. A relation extraction system was presented to extract four relations from the lymphoma corpus. The system achieved very good performance on the training set, with 100% F-score obtained by the rule-based module and 97.2% F-score attained by the support vector machines classifier. Rule-based approaches were used to generate the structured outputs and populate them to predefined templates. The rule-based system attained over 97% F-scores on the training sets. A pipeline system was implemented with an assembly of all the components described above. It achieved promising results in the end-to-end evaluations, with 86.5%, 84.2% and 78.9% F-scores on the melanoma, colorectal cancer and lymphoma test sets respectively

Understanding Health and Disease with Multidimensional Single-Cell Methods

Current efforts in the biomedical sciences and related interdisciplinary fields are focused on gaining a molecular understanding of health and disease, which is a problem of daunting complexity that spans many orders of magnitude in characteristic length scales, from small molecules that regulate cell function to cell ensembles that form tissues and organs working together as an organism. In order to uncover the molecular nature of the emergent properties of a cell, it is essential to measure multiple cell components simultaneously in the same cell. In turn, cell heterogeneity requires multiple cells to be measured in order to understand health and disease in the organism. This review summarizes current efforts towards a data-driven framework that leverages single-cell technologies to build robust signatures of healthy and diseased phenotypes. While some approaches focus on multicolor flow cytometry data and other methods are designed to analyze high-content image-based screens, we emphasize the so-called Supercell/SVM paradigm (recently developed by the authors of this review and collaborators) as a unified framework that captures mesoscopic-scale emergence to build reliable phenotypes. Beyond their specific contributions to basic and translational biomedical research, these efforts illustrate, from a larger perspective, the powerful synergy that might be achieved from bringing together methods and ideas from statistical physics, data mining, and mathematics to solve the most pressing problems currently facing the life sciences.Comment: 25 pages, 7 figures; revised version with minor changes. To appear in J. Phys.: Cond. Mat

Development and application of two novel monoclonal antibodies against overexpressed CD26 and integrin α3 in human pancreatic cancer.

Monoclonal antibody (mAb) technology is an excellent tool for the discovery of overexpressed cell surface tumour antigens and the development of targeting agents. Here, we report the development of two novel mAbs against CFPAC-1 human pancreatic cancer cells. Using ELISA, flow cytometry, immunoprecipitation, mass spectrometry, Western blot and immunohistochemistry, we found that the target antigens recognised by the two novel mAbs KU44.22B and KU44.13A, are integrin α3 and CD26 respectively, with high levels of expression in human pancreatic and other cancer cell lines and human pancreatic cancer tissue microarrays. Treatment with naked anti-CD26 mAb KU44.13A did not have any effect on the growth and migration of cancer cells nor did it induce receptor downregulation. In contrast, treatment with anti-integrin α3 mAb KU44.22B inhibited growth in vitro of Capan-2 cells, increased migration of BxPC-3 and CFPAC-1 cells and induced antibody internalisation. Both novel mAbs are capable of detecting their target antigens by immunohistochemistry but not by Western blot. These antibodies are excellent tools for studying the role of integrin α3 and CD26 in the complex biology of pancreatic cancer, their prognostic and predictive values and the therapeutic potential of their humanised and/or conjugated versions in patients whose tumours overexpress integrin α3 or CD26

Increased expression of autophagy protein LC3 in two patients with progressing chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is the most common type of adult leukemia in the western hemisphere. It is characterized by a clonal proliferation of a population of CD5+ B lymphocytes that accumulate in the secondary lymphoid tissues, bone marrow, and blood. Some CLL patients remain free of symptoms for decades, whereas others rapidly become symptomatic or develop high-risk disease. Studying autophagy, which may modulate key protein expression and cell survival, may be important to the search for novel prognostic factors and molecules. Here, we applied flow cytometry technology to simultaneously detect autophagy protein LC3B with classical phenotypical markers used for the identification of tumoral CLL B cell clones. We found that two patients with progressing CLL showed increased expression of the autophagy protein LC3B, in addition to positive expression of CD38 and ZAP70 and unmutated status of IGHV. Our data suggest that activation of autophagy flux may correlate with CLL progression even before Ibrutinib treatment.Fil: Arroyo, Daniela Soledad. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rodríguez, Cecilia Inés. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; ArgentinaFil: Bussi, Claudio. The Francis Crick Institute; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Manzone Rodriguez, Clarisa. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Córdoba. Centro de Investigaciones en Bioquímica Clínica e Inmunología; ArgentinaFil: Sastre, Darío. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Heller, Viviana. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Stanganelli, Carmen Graciela. Academia Nacional de Medicina de Buenos Aires. Instituto de Investigaciones Hematológicas "Mariano R. Castex"; ArgentinaFil: Slavutsky, Irma Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Iribarren, Pablo. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentin

GeneCount: genome-wide calculation of absolute tumor DNA copy numbers from array comparative genomic hybridization data

Absolute tumor DNA copy numbers can currently be achieved only on a single gene basis by using fluorescence in situ hybridization (FISH). We present GeneCount, a method for genome-wide calculation of absolute copy numbers from clinical array comparative genomic hybridization data. The tumor cell fraction is reliably estimated in the model. Data consistent with FISH results are achieved. We demonstrate significant improvements over existing methods for exploring gene dosages and intratumor copy number heterogeneity in cancers

Human surfactant protein D alters oxidative stress and HMGA1 expression to induce p53 apoptotic pathway in eosinophil leukemic cell line

This article is made available through the Brunel Open Access Publishing Fund. Copyright: © 2013 Mahajan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Surfactant protein D (SP-D), an innate immune molecule, has an indispensable role in host defense and regulation of inflammation. Immune related functions regulated by SP-D include agglutination of pathogens, phagocytosis, oxidative burst, antigen presentation, T lymphocyte proliferation, cytokine secretion, induction of apoptosis and clearance of apoptotic cells. The present study unravels a novel ability of SP-D to reduce the viability of leukemic cells (eosinophilic leukemic cell line, AML14.3D10; acute myeloid leukemia cell line, THP-1; acute lymphoid leukemia cell lines, Jurkat, Raji; and human breast epithelial cell line, MCF-7), and explains the underlying mechanisms. SP-D and a recombinant fragment of human SP-D (rhSP-D) induced G2/M phase cell cycle arrest, and dose and timedependent apoptosis in the AML14.3D10 eosinophilic leukemia cell line. Levels of various apoptotic markers viz. activated p53, cleaved caspase-9 and PARP, along with G2/M checkpoints (p21 and Tyr15 phosphorylation of cdc2) showed significant increase in these cells. We further attempted to elucidate the underlying mechanisms of rhSP-D induced apoptosis using proteomic analysis. This approach identified large scale molecular changes initiated by SPD in a human cell for the first time. Among others, the proteomics analysis highlighted a decreased expression of survival related proteins such as HMGA1, overexpression of proteins to protect the cells from oxidative burst, while a drastic decrease in mitochondrial antioxidant defense system. rhSP-D mediated enhanced oxidative burst in AML14.3D10 cells was confirmed, while antioxidant, N-acetyl-L-cysteine, abrogated the rhSP-D induced apoptosis. The rhSP-D mediated reduced viability was specific to the cancer cell lines and viability of human PBMCs from healthy controls was not affected. The study suggests involvement of SP-D in host’s immunosurveillance and therapeutic potential of rhSP-D in the eosinophilic leukemia and cancers of other origins.Department of Biotechnology, Indi