Velociraptor: Cross-Platform Quantitative Search Using Hallmark Cell Features.

A key challenge for single cell discovery analysis is to identify new cell types, describe them quantitatively, and seek these novel cells in new studies often using a different platform. Over the last decade, tools were developed to address identification and quantitative description of cells in human tissues and tumors. However, automated validation of populations at the single cell level has struggled due to the cytometry field's reliance on hierarchical, ordered use of features and on platform-specific rules for data processing and analysis. Here we present Velociraptor, a workflow that implements Marker Enrichment Modeling in three cross-platform modules: 1) identification of cells specific to disease states, 2) description of hallmark features for each cell and population, and 3) searching for cells matching one or more hallmark feature sets in a new dataset. A key advance is that Velociraptor registers cells between datasets, including between flow cytometry and quantitative imaging using different, overlapping feature sets. Four datasets were used to challenge Velociraptor and reveal new biological insights. Working at the individual sample level, Velociraptor tracked the abundance of clinically significant glioblastoma brain tumor cell subsets and characterized the cells that predominate in recurrent tumors as a close match for rare, negative prognostic cells originally observed in matched pre-treatment tumors. In patients with inborn errors of immunity, Velociraptor identified genotype-specific cells associated with GATA2 haploinsufficiency. Finally, in cross-platform analysis of immune cells in multiplex imaging of breast cancer, Velociraptor sought and correctly identified memory T cell subsets in tumors. Different phenotypic descriptions generated by algorithms or humans were shown to be effective as search inputs, indicating that cell identity need not be described in terms of per-feature cutoffs or strict hierarchical analyses. Velociraptor thus identifies cells based on hallmark feature sets, such as protein expression signatures, and works effectively with data from multiple sources, including suspension flow cytometry, imaging, and search text based on known or theoretical cell features.

IL-8 Instructs Macrophage Identity in Lateral Ventricle Contacting Glioblastoma.

Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, CD32+ HLA-DRhi macrophages were shown to have displaced resident microglia in GBM tumors that contact the lateral ventricle stem cell niche. Since these lateral ventricle contacting GBM tumors have especially poor outcomes, identifying the origin and role of these CD32+ macrophages is likely critical to developing successful GBM immunotherapies. Here, we identify these CD32+ cells as M_IL-8 macrophages and establish that IL-8 is sufficient and necessary for tumor cells to instruct healthy macrophages into CD32+ M_IL-8 M2 macrophages. In ex vivo experiments with conditioned medium from primary human tumor cells, inhibitory antibodies to IL-8 blocked the generation of CD32+ M_IL-8 cells. Finally, using a set of 73 GBM tumors, IL-8 protein is shown to be present in GBM tumor cells in vivo and especially common in tumors contacting the lateral ventricle. These results provide a mechanistic origin for CD32+ macrophages that predominate in the microenvironment of the most aggressive GBM tumors. IL-8 and CD32+ macrophages should now be explored as targets in combination with GBM immunotherapies, especially for patients whose tumors present with radiographic contact with the ventricular-subventricular zone stem cell niche.

Learning cell identity in immunology, neuroscience, and cancer.

Suspension and imaging cytometry techniques that simultaneously measure hundreds of cellular features are powering a new era of cell biology and transforming our understanding of human tissues and tumors. However, a central challenge remains in learning the identities of unexpected or novel cell types. Cell identification rubrics that could assist trainees, whether human or machine, are not always rigorously defined, vary greatly by field, and differentially rely on cell intrinsic measurements, cell extrinsic tissue measurements, or external contextual information such as clinical outcomes. This challenge is especially acute in the context of tumors, where cells aberrantly express developmental programs that are normally time, location, or cell-type restricted. Well-established fields have contrasting practices for cell identity that have emerged from convention and convenience as much as design. For example, early immunology focused on identifying minimal sets of protein features that mark individual, functionally distinct cells. In neuroscience, features including morphology, development, and anatomical location were typical starting points for defining cell types. Both immunology and neuroscience now aim to link standardized measurements of protein or RNA to informative cell functions such as electrophysiology, connectivity, lineage potential, phospho-protein signaling, cell suppression, and tumor cell killing ability. The expansion of automated, machine-driven methods for learning cell identity has further created an urgent need for a harmonized framework for distinguishing cell identity across fields and technology platforms. Here, we compare practices in the fields of immunology and neuroscience, highlight concepts from each that might work well in the other, and propose ways to implement these ideas to study neural and immune cell interactions in brain tumors and associated model systems.

Highly efficient and simple SSPER and rrPCR approaches for the accurate site-directed mutagenesis of large and small plasmids.

Advances are needed in the site-directed mutagenesis of large plasmids for protein structure-function studies, as current methods are often inefficient, complicated and time-consuming. Here two new methods are reported that overcome these difficulties, namely the single primer extension reaction (SSPER) strategy that reaches 100% efficiency and the reduce recycle PCR (rrPCR) method that is advantageous in generating single and pairwise combinations of mutations. Both methods are distinguished from current technologies by the addition of a step that easily removes the oligonucleotide primer(s) after the first reaction, thus allowing for the addition of a second reaction in chronological sequence to generate and isolate the appropriate DNA product with the site-directed mutation(s). High efficiency of the methods is demonstrated by generating single and paired combinations of the 11 site-directed mutations targeted on 5 different plasmid DNA templates ranging from 10 to 12 kb and 57-60% GC-content at a rate of 50-100%. Overall, the methods are demonstrated to be (i) highly accurate, allowing for screening of plasmids by DNA sequencing, (ii) streamlined to generate the mutations within a single day, (iii) cost-effective in requiring only two primers and two enzymes (DpnI and a proofreading DNA polymerase), (iv) straightforward in primer design, (v) applicable for both large and small plasmids, and (vi) easily implemented by entry level researchers.

Identification of a Unique Cytotoxic Thieno[2,3-c]Pyrazole Derivative with Potent and Selective Anticancer Effects In Vitro.

In recent years, the thienopyrazole moiety has emerged as a pharmacologically active scaffold with antitumoral and kinase inhibitory activity. In this study, high-throughput screening of 2000 small molecules obtained from the ChemBridge DIVERset library revealed a unique thieno[2,3-c]pyrazole derivative (Tpz-1) with potent and selective cytotoxic effects on cancer cells. Compound Tpz-1 consistently induced cell death at low micromolar concentrations (0.19 µM to 2.99 µM) against a panel of 17 human cancer cell lines after 24 h, 48 h, or 72 h of exposure. Furthermore, an in vitro investigation of Tpz-1's mechanism of action revealed that Tpz-1 interfered with cell cycle progression, reduced phosphorylation of p38, CREB, Akt, and STAT3 kinases, induced hyperphosphorylation of Fgr, Hck, and ERK 1/2 kinases, and disrupted microtubules and mitotic spindle formation. These findings support the continued exploration of Tpz-1 and other thieno[2,3-c]pyrazole-based compounds as potential small-molecule anticancer agents.

Three novel piperidones exhibit tumor-selective cytotoxicity on leukemia cells via protein degradation and stress-mediated mechanisms.

BACKGROUND: Cancer is an ongoing worldwide health problem. Although chemotherapy remains the mainstay therapy for cancer, it is not always effective and has detrimental side effects. Here, we present piperidone compounds P3, P4, and P5 that selectively target cancer cells via protein- and stress-mediated mechanisms. METHODS: We assessed typical apoptotic markers including phosphatidylserine externalization, caspase-3 activation, and DNA fragmentation through flow cytometry. Then, specific markers of the intrinsic pathway of apoptosis including the depolarization of the mitochondria and the generation of reactive oxygen species (ROS) were investigated. Finally, we utilized western blot techniques, RT-qPCR, and observed the cell cycle profile after compound treatment to evaluate the possible behavior of these compounds as proteasome inhibitors. For statistical analyses, we employed the one-way ANOVA followed by Bonferroni post hoc test. RESULTS: P3, P4, and P5 induce cytotoxic effects towards tumorigenic cells, as opposed to non-cancerous cells, at the low micromolar range. Compound treatment leads to the activation of the intrinsic pathway of apoptosis. The accumulation of poly-ubiquitinated proteins and the pro-apoptotic protein Noxa, both typically observed after proteasome inhibition, occurs after P3, P4, and P5 treatment. The stress-related genes PMAIP1, ATF3, CHAC1, MYC, and HMOX-1 were differentially regulated to contribute to the cytotoxic activity of P3-P5. Finally, compound P5 causes cell cycle arrest at the G2/M phase. CONCLUSION: Taken together, compounds P3, P4, and P5 exhibit strong potential as anticancer drug candidates as shown by strong cytotoxic potential, activation of the intrinsic pathway of apoptosis, and show typical proteasome inhibitor characteristics.

Functional characterization of six aspartate (D) recombinant mojastin mutants (r-Moj): A second aspartate amino acid carboxyl to the RGD in r-Moj-D_ peptides is not sufficient to induce apoptosis of SK-Mel-28 cells.

Disintegrins are small peptides produced in viper venom that act as integrin antagonists. When bound to integrins, disintegrins induce altered cellular behaviors, such as apoptotic induction. Disintegrins with RGDDL or RGDDM motifs induce apoptosis of normal and cancer cells. We hypothesized that a second aspartate (D) carboxyl to the RGD is sufficient to induce apoptosis. Five recombinant mojastin D mutants were produced by site-directed mutagenesis (r-Moj-DA, r-Moj-DG, r-Moj-DL, r-Moj-DN, and r-Moj-DV). Stable αv integrin knockdown and shRNA scrambled control SK-Mel-28 cell lines were produced to test a second hypothesis: r-Moj-D_ peptides bind to αv integrin. Only r-Moj-DL, r-Moj-DM, and r-Moj-DN induced apoptosis of SK-Mel-28 cells (at 29.4%, 25.6%, and 36.2%, respectively). Apoptotic induction was significantly reduced in SK-Mel-28 cells with a stable αv integrin knockdown (to 2%, 17%, and 2%, respectively), but not in SK-Mel-28 cells with a stable scrambled shRNA. All six r-Moj-D_ peptides inhibited cell proliferation; ranging from 49.56% (r-Moj-DN) to 75.6% (r-Moj-DA). Cell proliferation inhibition by r-Moj-D_ peptides was significantly reduced in SK-Mel-28 cells with a stable αv integrin knockdown. All six r-Moj-D_ peptides inhibited SK-Mel-28 cell migration at high levels (69%-100%). As a consequence, rac-1 mRNA expression levels were significantly reduced as early as 1 h after treatment, suggesting that rac-1 is involved in the cell migration activity of SK-Mel-28.