PD-1/L1 and CTLA-4 blockade immunotherapies have been approved for 13 types of cancers and are being studied in diffuse large B-cell lymphoma (DLBCL), the most common aggressive B-cell lymphoma. However, whether both PD-1 and CTLA-4 checkpoints are active and clinically significant in DLBCL is unknown. Whether PD-1 ligands expressed by tumor cells or by the microenvironment of DLBCL are critical for the PD-1 immune checkpoint is unclear. We performed immunophenotypic profiling for 405 patients with de novo DLBCL using a MultiOmyx immunofluorescence platform and simultaneously quantitated expression/coexpression of 13 immune markers to identify prognostic determinants. In both training and validation cohorts, results demonstrated a central role of the tumor immune microenvironment, and when its functionality was impaired by deficiency in tumor-infiltrating T cells and/or natural killer cells, high PD-1 expression (but not CTLA-4) on CD8+ T cells, or PD-L1 expression on T cells and macrophages, patients had significantly poorer survival after rituximab–CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) immunochemotherapy. In contrast, tumor-cell PD-L2 expression was associated with superior survival, as well as PD-L1+CD20+ cells proximal (indicates interaction) to PD-1+CD8+ T cells in patients with low PD-1+ percentage of CD8+ T cells. Gene-expression profiling results suggested the reversibility of T-cell exhaustion in PD-1+/PD-L1+ patients with unfavorable prognosis and implication of LILRA/B, IDO1, CHI3L1, and SOD2 upregulation in the microenvironment dysfunction with PD-L1 expression. This study comprehensively characterized the DLBCL immune landscape, deciphered the differential roles of various checkpoint components in rituximab–CHOP resistance in DLBCL patients, and suggests targets for PD-1/PD-L1 blockade and combination immunotherapies.
Intracranial pressure (ICP) is an important and established clinical measurement that is used in the management of severe acute brain injury. ICP waveforms are usually triphasic and are susceptible to artifact because of transient catheter malfunction or routine patient care. Existing methods for artifact detection include threshold-based, stability-based, or template matching, and result in higher false positives (when there is variability in the ICP waveforms) or higher false negatives (when the ICP waveforms lack complete triphasic components but are valid). We hypothesized that artifact labeling of ICP waveforms can be optimized by an active learning approach which includes interactive querying of domain experts to identify a manageable number of informative training examples. The resulting active learning based framework identified non-artifactual ICP pulses with a superior AUC of 0.96 ± 0.012, compared to existing methods: template matching (AUC: 0.71 ± 0.04), ICP stability (AUC: 0.51 ± 0.036) and threshold-based (AUC: 0.5 ± 0.02).
Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.
The movement of proteins within cells can provide dynamic indications of cell signaling and cell polarity, but methods are needed to track and quantify subcellular protein movement within tissue environments. Here we present a semiautomated approach to quantify subcellular protein location for hundreds of migrating cells within intact living tissue using retrovirally expressed fluorescent fusion proteins and time-lapse two-photon microscopy of intact thymic lobes. We have validated the method using GFP-PKCf, a marker for cell polarity, and LAT-GFP, a marker for T-cell receptor signaling, and have related the asymmetric distribution of these proteins to the direction and speed of cell migration. These approaches could be readily adapted to other fluorescent fusion proteins, tissues and biological questions. Keywords: two-photon microscopy; cell polarity; fluorescent fusion protein; image analysis; migration Recent advances in fluorescent imaging methods, together with the expanding use of genetically encoded fluorescent reporters, have dramatically enhanced our ability to probe dynamic events in vivo. In particular, two-photon microscopy of fluorescently labeled cells in living, three-dimensional (3-D) tissue has provided remarkable insights into cellular behavior in the immune system, the nervous system, and during embryonic development and tumorigenesis. [1][2][3][4][5][6] Most in vivo two-photon studies to date have utilized whole cell fluorescent labels and have focused on questions involving cell migration and cellular interactions. Along with advances in data acquisition, tools for imaging analysis are being developed, including commercial and open-source methods for cell tracking and quantifying cellular interactions from two-photon data sets. 5,7,8 The range of questions that can be addressed by two-photon imaging studies is expanding with the emerging use of fluorescent fusion proteins to mark intracellular structures, and examine their subcellular movement in vivo. 9,10 For example, T cells within migrating T-B cell conjugates in lymph nodes display stable accumulations of the T-cell antigen receptor signaling protein, linker for activation of T cells (LAT) at the site of contact with antigen bearing B cells, as revealed by the location of a fluorescent fusion protein between LAT and GFP (LAT-GFP). 9 The widespread application of this approach has been limited so far by the challenges of achieving a fluorescent signal bright enough for detection within tissues and within an appropriate number of cells, while maintaining normal physiology. Thus, there is a need to identify fluorescent fusion proteins, expression methods, and in vivo settings that are amenable to this approach.Another significant bottleneck in this approach is the lack of efficient methods for quantifying subcellular location of fluorescent signals from multicolor 3-D time-lapse data sets. Indeed, the published studies quantifying subcellular location of fluorescent fusion proteins have been limited to manual analysis of a small number of...
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