Deep Learning Prediction of Pathologic Complete Response in Breast Cancer Using MRI and Other Clinical Data: A Systematic Review.

Breast cancer patients who have pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) are more likely to have better clinical outcomes. The ability to predict which patient will respond to NAC early in the treatment course is important because it could help to minimize unnecessary toxic NAC and to modify regimens mid-treatment to achieve better efficacy. Machine learning (ML) is increasingly being used in radiology and medicine because it can identify relationships amongst complex data elements to inform outcomes without the need to specify such relationships a priori.

Physiological substrates and ontogeny-specific expression of the ubiquitin ligases MARCH1 and MARCH8.

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 . 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.

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

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.

Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response.

Purpose: This study used machine learning classification of texture features from MRI of breast tumor and peri-tumor at multiple treatment time points in conjunction with molecular subtypes to predict eventual pathological complete response (PCR) to neoadjuvant chemotherapy.

Materials And Method: This study employed a subset of patients (N = 166) with PCR data from the I-SPY-1 TRIAL (2002-2006). This cohort consisted of patients with stage 2 or 3 breast cancer that underwent anthracycline-cyclophosphamide and taxane treatment.

Convolutional Neural Network Detection of Axillary Lymph Node Metastasis Using Standard Clinical Breast MRI.

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.

MRI Volume Changes of Axillary Lymph Nodes as Predictor of Pathologic Complete Responses to Neoadjuvant Chemotherapy in Breast Cancer.

Introduction: Longitudinal monitoring of breast tumor volume over the course of chemotherapy is informative of pathologic response. This study aims to determine whether axillary lymph node (aLN) volume by magnetic resonance imaging (MRI) could augment the prediction accuracy of treatment response to neoadjuvant chemotherapy (NAC).

Materials And Methods: Level-2a curated data from the I-SPY-1 TRIAL (2002-2006) were used.

Protein profiles distinguish stable and progressive chronic lymphocytic leukemia.

Patients with a stable chronic lymphocytic leukemia (CLL) double their blood lymphocyte count in >5 years, but may develop progressive disease with lymphocytes doubling in <12 months. To identify a protein signature for progressive CLL, whole cell extracts of peripheral blood mononuclear cells from patients with CLL (n=27) were screened using iTRAQ (isobaric tags for relative and absolute quantification) analysis. A total of 84 differentially abundant proteins were identified from patients with stable and progressive CLL.

Analysis of Post-Liver Transplant Hepatitis C Virus Recurrence Using Serial Cluster of Differentiation Antibody Microarrays.

Background: 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.

Cell surface phenotype profiles distinguish stable and progressive chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is clinically heterogeneous. While some patients have indolent disease for many years, 20-30% will progress and ultimately die of their disease. CLL may be classified by the Rai or Binet staging system, mutational status of the immunoglobulin variable heavy-chain gene (IGVH), ZAP-70 overexpression, cytogenetic abnormalities (13q-, + 12, 11q-, 17p-) and expression of several cell surface antigens (CD38, CD49d) that correlate with risk of disease progression.

Profiles of surface mosaics on chronic lymphocytic leukemias distinguish stable and progressive subtypes.

Purpose: Chronic lymphocytic leukemia (CLL) is a heterogeneous disease, some patients may survive for many years, while 20-30% of patients progress and may die within several years. Currently, there is not a single procedure that enables accurate prognosis and triaging of those patients who need immediate and aggressive treatment. All CLL cells are characterised by the expression of the B-cell antigens CD19, CD20, CD21, CD22 and CD23, with aberrant expression of the T-cell antigen CD5.

Analysis of human liver disease using a cluster of differentiation (CD) antibody microarray.

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.

Surface profiles for subclassification of chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) has a variable clinical course. Some patients have stable disease while others progress and require treatment. Levels of several cluster of differentiation (CD) antigens are known to correlate with prognosis and may be used to stratify patients according to risk.

An extended antibody microarray for surface profiling metastatic melanoma.

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.

Surface antigen profiling of colorectal cancer using antibody microarrays with fluorescence multiplexing.

A procedure is described for the disaggregation of colorectal cancers (CRC) and normal intestinal mucosal tissues to produce suspensions of viable single cells, which are then captured on customized antibody microarrays recognising 122 different surface antigens (DotScan CRC microarray). Cell binding patterns recorded by optical scanning of microarrays provide a surface profile of antigens on the cells. Sub-populations of cells bound on the microarray can be profiled by fluorescence multiplexing using monoclonal antibodies tagged with Quantum Dots or other fluorescent dyes.

Cladribine and Fludarabine Nucleoside Change the Levels of CD Antigens on B-Lymphoproliferative Disorders.

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.

C-reactive protein, an 'intermediate phenotype' for inflammation: human twin studies reveal heritability, association with blood pressure and the metabolic syndrome, and the influence of common polymorphism at catecholaminergic/beta-adrenergic pathway loci.

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).

Analysis of human leukaemias and lymphomas using extensive immunophenotypes from an antibody microarray.

A novel antibody microarray has been developed that provides an extensive immunophenotype of leukaemia cells. The assay is a solid phase cell-capture technique in which 82 antigens are studied simultaneously. This paper presents the analysis of 733 patients with a variety of leukaemias and lymphomas from peripheral blood and bone marrow.

Multiplex detection of surface molecules on colorectal cancers.

A technique of fluorescence multiplexing is described for analysis of the plasma membrane proteome of colorectal cancer cells from surgically resected specimens, enabling detection and immunophenotyping when the cancer cells are in the minority. A single-cell suspension was prepared from a colorectal tumour, and the mixed population of cells was captured on a CD antibody microarray. The cancer cells were detected using a fluorescently tagged antibody for carcinoembryonic antigen (CEA-Alexa647) or epithelial cell adhesion marker (EpCAM-Alexa488).

Screening microarrays of novel monoclonal antibodies for binding to T-, B- and myeloid leukaemia cells.

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.

Identification of repertoires of surface antigens on leukemias using an antibody microarray.

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.