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Background Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the machine learning convolutional neural networks (CNNs) on multiparametric MRI to detect nodal metastasis with 18FDG-PET as ground truths. Materials and Methods Data were obtained via a retrospective search. Inclusion criteria were patients with bilateral breast MRI and 18FDG-PETand/or CT scans obtained before neoadjuvant chemotherapy. In total, 238 aLNs were obtained from 56 breast cancer patients with 18FDG-PET and/or CT and breast MRI data. Radiologists scored each node based on all MRI as diseased and non–diseased nodes. Five models were built using T1-W MRI, T2-W MRI, DCE MRI, T1-W + T2-W MRI, and DCE + T2-W MRI model. Performance was evaluated using receiver operating curve (ROC) analysis, including area under the curve (AUC). Results All CNN models yielded similar performance with an accuracy ranging from 86.08% to 88.50% and AUC ranging from 0.804 to 0.882. The CNN model using T1-W MRI performed better than that using T2-W MRI in detecting nodal metastasis. CNN model using combined T1- and T2-W MRI performed the best compared to all other models (accuracy = 88.50%, AUC = 0.882), but similar in AUC to the DCE + T2-W MRI model (accuracy = 88.02%, AUC = 0.880). All CNN models performed better than radiologists in detecting nodal metastasis (accuracy = 65.8%). Conclusion xxxxxx

MARCH1 and MARCH8 are ubiquitin ligases that control the expression and trafficking of critical immunoreceptors. Understanding of their function is hampered by three major knowledge gaps: (i) it is unclear which cell types utilize these ligases; (ii) their level of redundancy is unknown; and (iii) most of their putative substrates have been described in cell lines, often overexpressing MARCH1 or MARCH8, and it is unclear which substrates are regulated by either ligase in vivo. Here we address these questions by systematically analyzing the immune cell repertoire of MARCH1- or MARCH8-deficient mice, and applying unbiased proteomic profiling of the plasma membrane of primary cells to identify MARCH1 and MARCH8 substrates. Only CD86 and MHC II were unequivocally identified as immunoreceptors regulated by MARCH1 and MARCH8, but each ligase carried out its function in different tissues. MARCH1 regulated MHC II and CD86 in professional and “atypical” antigen presenting cells of hematopoietic origin, including neutrophils, eosinophils and monocytes. MARCH8 only operated in non-hematopoietic cells, such as thymic and alveolar epithelial cells. Our results establish the tissue-specific functions of MARCH1 and MARCH8 in regulation of immune receptor expression and reveal that the range of cells constitutively endowed with antigen-presentation capacity is wider than generally appreciated.

MARCH1 and MARCH8 are ubiquitin ligases that control the expression and trafficking of critical immunoreceptors. Understanding of their function is hampered by three major knowledge gaps: (i) it is unclear which cell types utilize these ligases; (ii) their level of redundancy is unknown; and (iii) most of their putative substrates have been described in cell lines, often overexpressing MARCH1 or MARCH8, and it is unclear which substrates are regulated by either ligase in vivo. Here we address these questions by systematically analyzing the immune cell repertoire of MARCH1- or MARCH8-deficient mice, and applying unbiased proteomic profiling of the plasma membrane of primary cells to identify MARCH1 and MARCH8 substrates. Only CD86 and MHC II were unequivocally identified as immunoreceptors regulated by MARCH1 and MARCH8, but each ligase carried out its function in different tissues. MARCH1 regulated MHC II and CD86 in professional and “atypical” antigen presenting cells of hematopoietic origin, whereas MARCH8 only operated in non-hematopoietic cells. Our results reveal that the range of cells constitutively endowed with antigen-presentation capacity is wider than generally appreciated. They also establish MARCH1 and MARCH8 as specialized regulators of CD4+ T cell immunity in two ontogenically distinct cellular compartments.

Background Axillary lymph node status is important for breast cancer staging and treatment planning as the majority of breast cancer metastasis spreads through the axillary lymph nodes. There is currently no reliable noninvasive imaging method to detect nodal metastasis associated with breast cancer. Materials and Methods Magnetic resonance imaging (MRI) data were those from the peak contrast dynamic image from 1.5 Tesla MRI scanners at the pre-neoadjuvant chemotherapy stage. Data consisted of 66 abnormal nodes from 38 patients and 193 normal nodes from 61 patients. Abnormal nodes were those determined by expert radiologist based on 18Fluorodeoxyglucose positron emission tomography images. Normal nodes were those with negative diagnosis of breast cancer. The convolutional neural network consisted of 5 convolutional layers with filters from 16 to 128. Receiver operating characteristic analysis was performed to evaluate prediction performance. For comparison, an expert radiologist also scored the same nodes as normal or abnormal. Results The convolutional neural network model yielded a specificity of 79.3% ± 5.1%, sensitivity of 92.1% ± 2.9%, positive predictive value of 76.9% ± 4.0%, negative predictive value of 93.3% ± 1.9%, accuracy of 84.8% ± 2.4%, and receiver operating characteristic area under the curve of 0.91 ± 0.02 for the validation data set. These results compared favorably with scoring by radiologists (accuracy of 78%). Conclusion The results are encouraging and suggest that this approach may prove useful for classifying lymph node status on MRI in clinical settings in patients with breast cancer, although additional studies are needed before routine clinical use can be realized. This approach has the potential to ultimately be a noninvasive alternative to lymph node biopsy.

Hepatitis C virus (HCV) reinfection of the liver allograft after transplantation is universal, with some individuals suffering severe disease recurrence. Predictive markers of recurrent disease severity are urgently needed. In this study, we used a cluster of differentiation (CD) microarray to predict the severity of HCV recurrence after transplantation.The CD antibody microarray assays of live leukocytes were performed on peripheral blood taken in the first year after transplantation. The results were grouped into phases defined as; Pre-transplant (day 0), Early (day 3 to week 2), Mid (week 4 to week 10), and Late (week 12 to week 26). Hepatitis C virus severity was based on fibrosis stages in the first 2 years (F0-1 mild and F2-4 severe).Serial blood samples from 16 patients were taken before and after liver transplantation. A total of 98 assays were performed. Follow-up was 3 years or longer. Comparing recurrence severity, significantly greater numbers of CD antigens were differentially expressed on the pretransplant samples compared to any posttransplant timepoints. Five differentially expressed CD antigens before transplantation (CD27 PH, CD182, CD260, CD41, and CD34) were significantly expressed comparing severe to mild recurrence, whereas expression of only CD152 was significant in the late phase after transplantation. No relationship was observed between the donor or recipient interleukin-28B genotypes and HCV recurrence severity.This study shows that circulating leukocyte CD antigen expression has utility in assessing recurrent HCV disease severity after liver transplantation and serves as a proof of principle. Importantly, pretransplant CD antigen expression is most predictive of disease outcome.

An antibody microarray was developed for profiling the surface proteome of melanoma cells, which may facilitate melanoma sub-classification and provide important prognostic information useful in predicting the clinical behavior of the melanoma (e.g., likely sites of metastatic spread), patient outcome and treatment response. Forty-eight antibodies were selected based on their correlation with melanoma development, progression and/or prognosis and printed on nitrocellulose slides. The immobilised antibodies capture live cells expressing corresponding antigens to produce a cell binding dot pattern representing the surface antigen profile (immunophenotype) of the melanoma. Surface antigen signatures were determined for a normal melanocyte and 6 melanoma cell lines and cell suspensions prepared from 10 surgically excised melanoma lymph node metastases. A procedure for obtaining separate surface antigen profiles for melanoma cells and leukocytes from clinical lymph node samples was also developed using anti-CD45 magnetic beads. The capture of live, bead-bound leukocytes on these antibody microarrays provides a significant enhancement of this microarray technology. The antibody microarray will be used to profile panels of surgically excised melanoma lymph node metastases (melanoma and leukocyte fractions) to determine whether the immunophenotypes correlate with clinicopathological characteristics, disease progression and clinical outcome.

We have developed a microarray (DotScan) that enables rapid immunophenotyping and classification of leukaemias and lymphomas by measuring the capture of cells by immobilized dots of 82 CD antibodies [Belov, L., de la Vega, O., dos Remedios, C.G., Mulligan, S.P., 2001. Immunophenotyping of leukemia using a cluster of differentiation antibody microarray. Cancer Res. 61, 4483; Belov, L., Huang, P., Barber, N., Mulligan, S.P., Christopherson, R.I., 2003. Identification of repertoires of surface antigens on leukemias using an antibody microarray. Proteomics 3, 2147]. The DotScan technology has been used to investigate the properties of 498 new antibodies submitted to the HLDA8 Workshop. These antibodies have been applied as 10 nl dots to a film of nitrocellulose on a microscope slide to make an HLDA8 microarray. After blocking the remaining nitrocellulose surface, individual arrays were incubated with each of 7 cell types from a human leukaemia cell panel consisting of three cell lines, CCRF-CEM (a T-cell acute lymphocytic leukaemia), MEC-1 (derived from B-cell chronic lymphocytic leukaemia) and HL-60 (a promyelocytic leukaemia), and four leukaemias from patients: a T-cell prolymphocytic leukaemia, a B-cell chronic lymphocytic leukaemia, and two acute myeloid leukaemias. Leukaemia cells were captured by those immobilized antibodies for which they expressed the corresponding surface molecule. Unbound cells were gently washed off, bound cells were fixed to the arrays and dot patterns were recorded using a DotScan array reader and quantified using DotScan data analysis software. The data obtained show the unique expression profiles of the 7 cell types in the leukaemia cell panel obtained with the DotScan microarray, and the differential capture patterns for these 7 cell types screened against the 498 antibodies in the HLDA8 microarray constructed for this study.

Background: A CD antibody microarray has been previously developed allowing semi-quantitative identification of greater than 80 CD antigens on circulating leucocytes from peripheral blood samples. This assay, which uses a live cell-capture technique, enables an extensive leucocyte immunophenotype determination in a single analysis and to date this has been used successfully to characterise diseases including human leukaemias and HIV infection. Aims: To determine CD antigen expression profiles for patients with various liver diseases and to look for preserved disease-specific signatures. Methods: Three liver disease groups including hepatitis C (HCV) (n = 35), non-alcoholic steatohepatitis (NASH) (n = 21) and alcohol-related liver disease (n = 14) were compared with a normal group (n = 23). Hierarchal Clustering (HCL) and Principal Component Analysis (PCA) of the data revealed distinct binding patterns for patients with and without cirrhosis. Results: Patients with cirrhosis and portal hypertension compared with those without cirrhosis had significantly reduced expression of several markers of T-cell function including CD45, CD8, CD28 and TCR a/b. Disease prediction algorithms based on the expression data were able to discriminate cirrhotics from non-cirrhotics with 71% overall success, which improved to 77% when only patients with HCV were considered. Conclusions: These results demonstrate disease-specific consensus patterns of expression of CD antigens for patients with chronic liver disease, suggesting that the CD antibody array is a promising tool in the analysis of human liver disease, and with further refinement may have future research and clinical utility.

The purine analogs, fludarabine nucleoside (FdA), and cladribine (CdA) (1 μM, 24 hours), significantly changed the levels of some surface antigens on the human B-cell lines MEC2 and Raji. Changes in the surface proteins were identified using a Cluster of Differentiation (CD) antibody microarray that captures live cells and confirmed by flow cytometry. For Raji cells, CdA up-regulated CD10, CD54, CD80, and CD86, with repression of CD22, while FdA up-regulated CD20, CD54, CD80, CD86 and CD95. For MEC2 cells, CdA up-regulated CD11a, CD20, CD43, CD45, CD52, CD54, CD62L, CD80, CD86, and CD95, but FdA had no effect. Up-regulation of particular CD antigens induced on a B-cell lymphoproliferative disorder by a purine analog could provide targets for therapeutic antibodies with synergistic cell killing.

BACKGROUND C-reactive protein (CRP) both reflects and participates in inflammation, and its circulating concentration marks cardiovascular risk. Here we sought to understand the role of heredity in determining CRP secretion. METHODS CRP, as well as multiple facets of the metabolic syndrome, were measured in a series of 229 twins, both monozygotic (MZ) and dizygotic (DZ), to estimate trait heritability (h2). Single nucleotide polymorphism (SNP) genotyping was done at adrenergic pathway loci. Haplotypes were inferred from genotypes by likelihood methods. Association of CRP with hypertension and the metabolic syndrome was studied in a larger series of 732 individuals, including 79 with hypertension. RESULTS MZ and DZ twin variance components indicated substantial h2 for CRP, at approximately 56 +/- 7% (P < 0.001). CRP was significantly associated (P < 0.05) with multiple features of the metabolic syndrome in twins, including body mass index (BMI), blood pressure (BP), leptin and lipids. In established hypertension, elevated CRP was associated with increased BP, BMI, insulin, HOMA (index of insulin resistance), leptin, triglycerides and norepinephrine. Twin correlations indicated pleiotropy (shared genetic determination) for CRP with BMI (P = 0.0002), leptin (P < 0.001), triglycerides (P = 0.002) and systolic blood pressure (SBP) (P = 0.042). Approximately 9800 genotypes (43 genetic variants at 17 loci) were scored within catecholaminergic pathways: biosynthetic, receptor and signal transduction. Plasma CRP concentration in twins was predicted by polymorphisms at three loci in physiological series within the catecholamine biosynthetic/beta-adrenergic pathway: TH (tyrosine hydroxylase), ADRB1 (beta1-adrenergic receptor) and ADRB2 (beta2-adrenergic receptor). In the TH promoter, common allelic variation accounted for up to approximately 6.6% of CRP inter-individual variance. At ADRB1, variation at Gly389Arg predicted approximately 2.8% of CRP, while ADRB2 promoter variants T-47C and T-20C also contributed. Particular haplotypes and diplotypes at TH and ADRB1 also predicted CRP, though typically no better than single SNPs alone. Epistasis (gene-by-gene interaction) was demonstrated for particular combinations of TH and ADRB2 alleles, consistent with their actions in a pathway in series. In an illustration of pleiotropy, not only CRP but also plasma triglycerides were predicted by polymorphisms at TH (P = 0.0053) and ADRB2 (P = 0.027). CONCLUSIONS CRP secretion is substantially heritable in humans, demonstrating pleiotropy (shared genetic determination) with other features of the metabolic syndrome, such as BMI, triglycerides or BP. Multiple, common genetic variants in the catecholaminergic/beta-adrenergic pathway contribute to CRP, and these variants (especially at TH and ADRB2) seem to interact (epistasis) to influence the trait. The results uncover novel pathophysiological links between the adrenergic system and inflammation, and suggest new strategies to probe the role and actions of inflammation within this setting.

We have previously described a microarray of cluster of differentiation (CD) antibodies that enables concurrent determination of more than 60 CD antigens on leukocytes. This procedure does not require protein purification or labeling, or a secondary detection system. Whole cells are captured by a microarray of 10 nL antibody dots immobilized on a nitrocellulose film on a microscope slide. Distinct patterns of cell binding are observed for different leukemias or lymphomas. These haematological malignancies arise from precursor cells of T- or B-lymphocytic, or myeloid lineages of hematopoiesis. The dot patterns obtained from patients are distinct from those of peripheral blood leukocytes from normal subjects. This microarray technology has recently undergone a number of refinements. The microarray now contains more CD antibodies, and a scanner for imaging dot patterns and software for data analysis provide an extensive immunophenotype sufficient for diagnosis of common leukemias. The technology is being evaluated for diagnosis of leukemias with parallel use of conventional diagnostic criteria.