Proteomic characterisations of ulcerative colitis endoscopic biopsies associate with clinically relevant histological measurements of disease severity.

Aims And Methods: Accurate protein measurements using formalin-fixed biopsies are needed to improve disease characterisation. This feasibility study used targeted and global mass spectrometry (MS) to interrogate a spectrum of disease severities using 19 ulcerative colitis (UC) biopsies.

Results: Targeted assays for CD8, CD19, CD132 (interleukin-2 receptor subunit gamma/common cytokine receptor gamma chain), FOXP3 (forkhead box P3) and IL17RA (interleukin 17 receptor A) were successful; however, assays for IL17A (interleukin 17A), IL23 (p19) (interleukin 23, alpha subunit p19) and IL23R (interleukin 23 receptor) did not permit target detection.

Cell signaling-based classifier predicts response to induction therapy in elderly patients with acute myeloid leukemia.

Single-cell network profiling (SCNP) data generated from multi-parametric flow cytometry analysis of bone marrow (BM) and peripheral blood (PB) samples collected from patients >55 years old with non-M3 AML were used to train and validate a diagnostic classifier (DXSCNP) for predicting response to standard induction chemotherapy (complete response [CR] or CR with incomplete hematologic recovery [CRi] versus resistant disease [RD]). SCNP-evaluable patients from four SWOG AML trials were randomized between Training (N = 74 patients with CR, CRi or RD; BM set = 43; PB set = 57) and Validation Analysis Sets (N = 71; BM set = 42, PB set = 53). Cell survival, differentiation, and apoptosis pathway signaling were used as potential inputs for DXSCNP.

Development and validation of a single-cell network profiling assay-based classifier to predict response to induction therapy in paediatric patients with de novo acute myeloid leukaemia: a report from the Children's Oncology Group.

Single cell network profiling (SCNP) is a multi-parameter flow cytometry technique for simultaneous interrogation of intracellular signalling pathways. Diagnostic paediatric acute myeloid leukaemia (AML) bone marrow samples were used to develop a classifier for response to induction therapy in 53 samples and validated in an independent set of 68 samples. The area under the curve of a receiver operating characteristic curve (AUC(ROC)) was calculated to be 0·85 in the training set and after exclusion of induction deaths, the AUC(ROC) of the classifier was 0·70 (P = 0·02) and 0·67 (P = 0·04) in the validation set when induction deaths (intent to treat) were included.

Single cell network profiling assay in bladder cancer.

The aim of this study was to assess the feasibility of applying the single cell network profiling (SCNP) assay to the examination of signaling networks in epithelial cancer cells, using bladder washings from 29 bladder cancer (BC) and 15 nonbladder cancer (NC) subjects. This report describes the methods we developed to detect rare epithelial cells (within the cells we collected from bladder washings), distinguish cancer cells from normal epithelial cells, and reproducibly quantify signaling within these low frequency cancer cells. Specifically, antibodies against CD45, cytokeratin, EpCAM, and cleaved-PARP (cPARP) were used to differentiate nonapoptotic epithelial cells from leukocytes, while measurements of DNA content to determine aneuploidy (DAPI stain) allowed for distinction between tumor and normal epithelial cells.