TRKA expression and gene copy number across solid tumours.

Aims: Neurotrophic Tropomyosin Kinase Receptor 1 () gene encodes for the protein Tropomyosin-related kinase A (TRKA). Deregulated activity of TRKA has been shown to have oncogenic potential. We present here the results of an immunohistochemical (IHC) observational cohort study of TRKA expression together with gene copy number (GCN) assessment in various solid tumours.

Molecular Profiling of Mammary Analog Secretory Carcinoma Revealed a Subset of Tumors Harboring a Novel ETV6-RET Translocation: Report of 10 Cases.

ETV6 gene abnormalities are well described in tumor pathology. Many fusion partners of ETV6 have been reported in a variety of epithelial, mesenchymal, and hematological malignancies. In salivary gland tumor pathology, however, the ETV6-NTRK3 translocation is specific for (mammary analog) secretory carcinoma, and has not been documented in any other salivary tumor type.

AngioMap is a novel image analysis algorithm for assessment of plasma cell distribution within bone marrow vascular niche.

The ability to characterize distribution of neoplastic hematopoietic cells and their progenitors in their native microenvironment is emerging as an important challenge and potential therapeutic target in many disease areas, including multiple myeloma. In multiple myeloma, bone marrow (BM) angiogenesis is typically increased and microvessel density is a known indicator of poor prognosis. However, the difficulty of consistently measuring 3D vessels from 2D cut sections has previously limited the study of spatial distribution of plasma cells (PC) and their interaction with BM microenvironment.

Tissue pattern recognition error rates and tumor heterogeneity in gastric cancer.

The anatomic pathology discipline is slowly moving toward a digital workflow, where pathologists will evaluate whole-slide images on a computer monitor rather than glass slides through a microscope. One of the driving factors in this workflow is computer-assisted scoring, which depends on appropriate selection of regions of interest. With advances in tissue pattern recognition techniques, a more precise region of the tissue can be evaluated, no longer bound by the pathologist's patience in manually outlining target tissue areas.

Evaluating tumor heterogeneity in immunohistochemistry-stained breast cancer tissue.

Quantitative clinical measurement of heterogeneity in immunohistochemistry staining would be useful in evaluating patient therapeutic response and in identifying underlying issues in histopathology laboratory quality control. A heterogeneity scoring approach (HetMap) was designed to visualize a individual patient's immunohistochemistry heterogeneity in the context of a patient population. HER2 semiquantitative analysis was combined with ecology diversity statistics to evaluate cell-level heterogeneity (consistency of protein expression within neighboring cells in a tumor nest) and tumor-level heterogeneity (differences of protein expression across a tumor as represented by a tissue section).

Multiplexed measurement of proteins in tissue in a clinical environment.

There is an emerging need for more effective approaches to accurately quantitate protein expression in tissue samples. In many clinical studies and particularly in pharmaceutical clinical trials, access to adequate tissue samples is a major bottleneck, and thus techniques to measure protein expression in these valuable tissue specimens is important. This study will review current approaches in multiplexing of protein expression in tissue, and discusses new approaches using a novel image registration technique across multiple tissue sections.

The role and impact of quantitative discovery pathology.

The decision to advance an early-stage compound into formal preclinical testing depends on confidence in mechanism, efficacy and toxicity profiles. A substantial percentage of this confidence comes from histopathology interpretation, as the local tissue environment contains strong signals of both efficacy and toxicity. Accessing this tissue information is made difficult by biological variability across organs and tissues, an insufficient pool of pathology experts working in discovery, and the high subjectivity and individual isolation of microscope-based observations.

Digital pathology in drug discovery and development: multisite integration.

Digital pathology is an emerging technology that provides an image-based environment for managing and interpreting the information generated from a digitized glass slide, offering substantial improvements in pharmaceutical drug development across discovery, preclinical GLP pathology and oncology clinical trials. Digital pathology is transforming global pharmaceutical research by enabling data sharing to integrate dispersed pharma pathology labs around the world. This article reviews the stages of multisite digital pathology integration in large pharmaceutical companies, offering suggestions for success and highlighting challenges.

Basis for resistance to imatinib in 16 BCR-ABL mutants as determined using molecular dynamics.

Large-scale (approximately 36,000 atoms) long-time (30 ns each) molecular dynamics (MD) simulations on the complex of imatinib and 16 common mutants of the ABL tyrosine kinase domain have been performed to study the imatinib resistance mechanisms at the atomic level. MD simulations show that long time computational simulations could offer insight information that static models, simple homology modeling methods, or short-time simulations cannot provide for the BCR-ABL imatinib resistance problem. Three possible types of mutational effects from those mutants are found: the direct effect on the contact interaction with imatinib (e.

Proteomics-based prediction of clinical response in acute myeloid leukemia.

Objective: Response to chemotherapy is achieved in 60% to 70% of patients with acute myeloid leukemia. The ability to predict responders may help in stratifying patients and exploring different therapeutic approaches for nonresponders. Proteomics methods were used to search for predictive factors or combinations of factors.

Molecular basis explanation for imatinib resistance of BCR-ABL due to T315I and P-loop mutations from molecular dynamics simulations.

Background: Computational simulations have become powerful tools for understanding detailed interactions in biologic systems. To the authors' knowledge to date, the mechanism of imatinib resistance in BCR-ABL has not been clarified at the atomic level, and computational studies are required.

Methods: Molecular dynamics (MD) simulations on the complex of imatinib with the wild-type, T315I mutant, and 10 other P-loop mutants of the tyrosine kinase BCR-ABL were performed to study the mechanism of imatinib resistance.

Development of a novel, accurate, automated, rapid, high-throughput technique suitable for population-based carrier screening for Fragile X syndrome.

Purpose: To develop a high-throughput, automated, accurate method suitable for population-based carrier detection of fragile X syndrome.

Methods: We developed a new method called capillary Southern analysis that allows automated high-throughput screening for expanded fragile X mental retardation 1 (FMR1) alleles. Initially samples are analyzed by a multiplex polymerase chain reaction that contains an internal control to establish gender.

Proteomic-based prediction of clinical behavior in adult acute lymphoblastic leukemia.

Background: Response in adult acute lymphoblastic leukemia (ALL) can be achieved in a majority of patients. However, unlike pediatric ALL, recurrence is common in adult ALL, and the ability to predict at an early stage which patients are most likely to experience recurrence may help in devising new therapeutic approaches to prevent recurrence.

Methods: Peripheral blood plasma from 57 patients with confirmed ALL was obtained before induction therapy for proteomic analysis.

Challenges of target/compound data integration from disease to chemistry: a case study of dihydrofolate reductase inhibitors.

Despite the improvements in informatics associated with initiatives in the structure-based design and genomics fields, no straight-forward links are available between a given disease class and drug chemistry. This involves effective linking of disease to protein targets, and then mapping these targets to drug chemistry. In practice, protein-ligand structural analyses and high-throughput screening experiments generate the links between targets implicated in disease and chemical leads.

Multiple property tolerance analysis for the evaluation of missense mutations.

Computational prediction of the impact of a mutation on protein function is still not accurate enough for clinical diagnostics without additional human expert analysis. Sequence alignment-based methods have been extensively used but their results highly depend on the quality of the input alignments and the choice of sequences. Incorporating the structural information with alignments improves prediction accuracy.