ALBERT

Description: Background: Nuclear receptors (NRs) form a large family of ligand-inducible transcription factors that regulate gene expressions involved in numerous physiological phenomena, such as embryogenesis, homeostasis, cell growth and death. These nuclear receptors-related pathways are important targets of marketed drugs. Therefore, the design of a reliable computational model for predicting NRs from amino acid sequence has now been a significant biomedical problem. Results: Conjoint triad feature (CTF) mainly considers neighbor relationships in protein sequences by encoding each protein sequence using the triad (continuous three amino acids) frequency distribution extracted from a 7-letter reduced alphabet. In addition, chaos game representation (CGR) can investigate the patterns hidden in protein sequences and visually reveal previously unknown structure. In this paper, three methods, CTF, CGR, amino acid composition (AAC), are applied to formulate the protein samples. By considering different combinations of three methods, we study seven groups of features, and each group is evaluated by the 10-fold cross-validation test. Meanwhile, a new non-redundant dataset containing 474 NR sequences and 500 non-NR sequences is built based on the latest NucleaRDB database. Comparing the results of numerical experiments, the group of combined features with CTF and AAC gets the best result with the accuracy of 96.30 % for identifying NRs from non-NRs. Moreover, if it is classified as a NR, it will be further put into the second level, which will classify a NR into one of the eight main subfamilies. At the second level, the group of combined features with CTF and AAC also gets the best accuracy of 94.73 %. Subsequently, the proposed predictor is compared with two existing methods, and the comparisons show that the accuracies of two levels significantly increase to 98.79 % (NR-2L: 92.56 %; iNR-PhysChem: 98.18 %; the first level) and 93.71 % (NR-2L: 88.68 %; iNR-PhysChem: 92.45 %; the second level) with the introduction of our CTF-based method. Finally, each component of CTF features is analyzed via the statistical significant test, and a simplified model only with the resulting top-50 significant features achieves accuracy of 95.28 %. Conclusions: The experimental results demonstrate that our CTF-based method is an effective way for predicting nuclear receptor proteins. Furthermore, the top-50 significant features obtained from the statistical significant test are considered as the “intrinsic features” in predicting NRs based on the analysis of relative importance.

Description: A membrane-free fluidized-bed microbial fuel cell (FB-MFC) was applied to investigate the effects of fluidization parameters on its electrogenesis capacity. Active carbon particles were found to significantly decrease the start-up time and increase the output voltage of the FB-MFC. The fluidization behavior of the active carbon particles in the FB-MFC reactor is one of the key parameters that influence the generation of electricity. With the FB-MFC operating under optimal conditions, maximum power density with minimal internal resistance of the MFC could be obtained. The FB-MFC could be operated in large-scale wastewater treatment processes with high chemical oxygen demand removal efficiencies. The ability to generate power with bacteria in wastewater makes microbial fuel cells (MFCs) promising alernatives in enhancing wastewater treatment processes. A fluidized-bed MFC is employed to investigate the effects of fluidization parameters on the electrogenesis capacity. Active carbon particles can significantly reduce the start-up time and increase the output voltage of the fuel cell.

Description: In follicular lymphoma (FL), clinical progression/histologic transformation occurs as a result of emergence of biologically aggressive malignant clones that escape the immune response. Whether such clones are preexisting or arise as a consequence of spontaneous or therapy-induced DNA mutation/genomic instability remains an open question; however, it has become increasingly clear that it will be important to understand the multi-clonal structure of tumors in order to treat them more effectively. As well, tumor-infiltrating immune cells represent a complex and heterogeneous population and are hypothesized to either help or hinder tumor progression. Several studies have searched for prognostic value in various infiltrating immune cell subsets, but results have been inconsistent, likely in part because most studies focus only on a few, incompletely characterized subsets at a time. Furthermore, the potential for co-variance between malignant subclones and the complement of infiltrating immune cells has not yet been explored. We would propose that understanding the entire tumor "ecosystem" in FL is needed to make further strides in predicting biological behavior and ultimately in guiding selection of the most appropriate of available rational therapies. In this study, we sought to use mass cytometry (CyTOF) to characterize both the clonal substructure of malignant populations and the infiltrating immune repertoire with unparalleled breadth, yet at single-cell resolution. We designed and optimized a 2-tube, 40-parameter CyTOF panel in which one tube is dedicated to characterizing population substructure among malignant B-cells and the other to profiling the composition of the infiltrating T-cell repertoire. We accessed viably frozen single cell suspensions from excess lymph node biopsy material remaining after diagnostic flow cytometry have been prospectively banked for the past 2 decades. We stained 12 FL, 23 diffuse large B-cell lymphoma (DLBCL), and 5 reactive lymph node (rLN) samples using the B-cell marker tube, acquired CyTOF data, and performed analyses using tSNE and Complicity mapping algorithms, which led us to make the following observations: First, over half of FL samples contain at least two phenotypically distinct tumor subclones. In contrast, very few of the DLBCL samples that we have examined thus far exhibit definitive phenotypic subclones. Lower intra-tumoral heterogeneity in DLBCL may imply that these tumors represent outgrowth of a highly evolved, dominant clone as compared to a less evolved collection of "untested" clones in FL. Second, tSNE mapping of FL tumors revealed two distinct subtypes, one in which the individual tumors showed highly similar and partially overlapping phenotypes that localized in proximity to normal germinal center B cells ("GC" subtype), and the other which was composed of more phenotypically heterogeneous tumors that were localized more distantly from normal germinal center B cells ("non-GC" subtype). We also stained 6 FL and 5 rLN samples using the T-cell marker tube, acquired CyTOF data, and performed analysis using tSNE and Scaffold mapping algorithms. We found the relative abundance of T-cells in FL samples was comparable to rLN (36.1% vs. 37.4% of total cells, p=0.90); however, most of the FL samples showed elevated CTL fractions (20.1% vs. 13.0% of total T-cells, p=0.02). Using Scaffold mapping, we were able to resolve a dramatic diversity of T and T/NK cell subsets, each of whose abundance varied substantially from one sample to the next. For example, the majority of CTL cells in rLN samples exhibited a relatively homogeneous, naïve-like phenotype, while CTL cells in FL typically contained a heterogeneous mixture of activated and exhausted subsets. The T-helper compartment exhibited a similar picture with relative population homogeneity within rLN samples, contrasting with heterogeneity within FL samples. Composite analysis correlating B- and T-cell features within the same FL specimen revealed that loss of HLA-DR and CD124 on malignant cells was correlated with CTL exhaustion, suggesting a potential immune escape mechanism. Our findings illustrate that novel information is revealed by 40-dimensional CyTOF analysis and provide insight into important, but understudied aspects of intra-tumoral heterogeneity and variable host immune response in lymphoma. Disclosures Scott: Janssen: Consultancy; Celgene: Consultancy; BC Cancer Agency: Patents & Royalties: Inventor on a patent licensed to NanoString Technologies; Roche: Honoraria.

Description: Background: Recent work in both hematologic malignancies and solid tumors has supported the notion that human cancers exhibit marked intra-tumoral heterogeneity (ITH). Results from next generation sequencing (NGS) studies support that subclonal DNA mutations underlie genotypic ITH within a single tumor since the majority of sequence variants are present in only 5-50% of reads for a given tumor sample, and single cell analyses have shown that individual tumor subclones may be ancestrally related in a complex branching hierarchy, suggesting that therapy failures and progressive disease likely arise by Darwinian selection for more aggressive or therapy resistant clones. It has become increasingly clear that it will be important to understand the multi-clonal structure of tumors in order to treat them more effectively. In this study, we sought to use time-of-flight mass cytometry (CyTOF) to explore clonal phenotypic substructure in diffuse large B-cell lymphoma (DLBCL), a diagnostic entity notorious for clinical heterogeneity. Methods: We examined viably frozen single cell suspensions from diagnostic lymph node biopsy samples received for flow cytometric analysis at the BC Cancer Agency. We have thus far acquired CyTOF data from 25 cases of DLBCL using a two-tube, 40-parameter panel encompassing a total of 58 different markers including both surface and intracellular antigens that were selected to reveal heterogeneity within the malignant B-cell population. For each sample acquisition, we included "spiked-in" control cells from pooled reactive (non-malignant) lymph node samples to control for staining variation between antibody/reagent lots and also run-to-run CyTOF instrument drift, facilitated by a CD45 antibody "barcoding" approach. We analyzed the data using a combination of viSNE, Isomap, and PhenoGraph analysis packages. Results: Analysis of individual tumor samples readily distinguished between malignant and residual normal B-cell populations, and also revealed distinct subpopulations among malignant cells of varying degrees of relatedness to one another. These subpopulations were then sorted from one another by conventional FACS from parallel vials of cryopreserved cells using lower dimensional sorting strategies derived from the 40-parameter CyTOF data. Sorted subpopulations will be analyzed by targeted amplicon sequencing for single nucleotide variants identified from whole exome sequencing data obtained from unsorted material to explore the hypothesis that these may represent genotypic subclones. 
Analysis of multiple tumor samples at once yielded several observations. First, B-cells from reactive lymph nodes and non-malignant B-cells within patient lymphoma specimens reproducibly cluster atop one another, indicating highly similar if not identical phenotypic profiles. Second, the majority of patient DLBCL tumors form cohesive individual clusters, separate and distinct from one another, suggesting that the 40-dimensional panel defines cell populations with sufficient resolution such that each patient's tumor can be uniquely identified. Third, individual DLBCL tumors do not aggregate in tight proximity with one another to the extent that we observe among patient follicular lymphoma (FL) samples, suggesting DLBCL represents a broader diversity of phenotypic classes. Fourth, there is local, but loose aggregation of ABC versus GCB subtypes, but there are also clear outliers and areas of intermingling between ABC and GCB tumors, as defined by immunohistochemistry. Finally, a subset of DLBCL tumors exhibit minor subpopulations that map apart from their corresponding "parent" tumor populations, but yet overlap one another, raising the possibility of divergent evolution away from (or alternatively convergent evolution towards) a common tumor archetype. Conclusions: 
Taken together, these observations support that novel information can be derived from CyTOF data with important implications for our understanding of both intra- and inter-tumoral heterogeneity in DLBCL. Disclosures Scott: Celgene: Consultancy, Honoraria; NanoString: Patents & Royalties: Inventor on a patent that NanoString has licensed.