Nodal-Stage Classification in Invasive Lobular Breast Carcinoma: Influence of Different Interpretations of the pTNM Classification

Purpose Application of current nodal status classification is complicated in lobular breast carcinoma metastases. The aim of this study was to define the optimal interpretation of the pTNM classification in sentinel node (SN) -positive patients to select patients with limited or with a high risk of non-SN involvement. Patients and Methods SN metastases of 392 patients with lobular breast carcinoma were reclassified according to interpretations of the European Working Group for Breast Screening Pathology (EWGBSP) and guidelines by Turner et al, and the predictive power for non-SN involvement was assessed. Results Reclassification according to definitions of EWGBSP and Turner et al resulted in different pN classification in 73 patients (19%). The rate of non-SN involvement in the 40 patients with isolated tumor cells according to Turner et al and with micrometastases according to EWGBSP was 20%, which is comparable to the established rate for micrometastases. The rate of non-SN involvement in the 29 patients with micrometastases according to Turner et al and with macrometastases according to EWGBSP was 48%, which is comparable to the established rate for macrometastases. Therefore, the EWGBSP method to classify SN tumor load better reflected the risk of non-SN involvement than the Turner et al system. Conclusion Compared with the guidelines by Turner et al, the EWGBSP definitions better reflect SN metastatic tumor load and allow better differentiation between patients with lobular breast carcinoma who have a limited or a high risk of non-SN metastases. Therefore, we suggest using the EWGBSP definitions in these patients to select high-risk patients who may benefit from additional local and/or systemic therapy

Nucleic acid extraction from formalin-fixed paraffin-embedded cancer cell line samples: a trade off between quantity and quality?

Background: Advanced genomic techniques such as Next-Generation-Sequencing (NGS) and gene expression profiling, including NanoString, are vital for the development of personalised medicines, as they enable molecular disease classification. This has become increasingly important in the treatment of cancer, aiding patient selection. However, it requires efficient nucleic acid extraction often from formalin-fixed paraffin-embedded tissue (FFPE). Methods: Here we provide a comparison of several commercially available manual and automated methods for DNA and/or RNA extraction from FFPE cancer cell line samples from Qiagen, life Technologies and Promega. Differing extraction geometric mean yields were evaluated across each of the kits tested, assessing dual DNA/RNA extraction vs. specialised single extraction, manual silica column based extraction techniques vs. automated magnetic bead based methods along with a comparison of subsequent nucleic acid purity methods, providing a full evaluation of nucleic acids isolated. Results: Out of the four RNA extraction kits evaluated the RNeasy FFPE kit, from Qiagen, gave superior geometric mean yields, whilst the Maxwell 16 automated method, from Promega, yielded the highest quality RNA by quantitative real time RT-PCR. Of the DNA extraction kits evaluated the PicoPure DNA kit, from Life Technologies, isolated 2–14× more DNA. A miniaturised qPCR assay was developed for DNA quantification and quality assessment. Conclusions: Careful consideration of an extraction kit is necessary dependent on quality or quantity of material required. Here we provide a flow diagram on the factors to consider when choosing an extraction kit as well as how to accurately quantify and QC the extracted material

Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named ‘Immunoscore’ has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune). © 2013 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland

Inhibition of Caveolin-1 Restores Myeloid Cell Function in Human Glioblastoma

Background: Gliomas are the most common primary brain tumor in both children and adults. The prognosis for glioblastoma (GBM), the most common type of malignant glioma, has remained dismal, with median survival a little over one year despite maximal therapy with surgery, chemotherapy, and radiation. Although immunotherapy has become increasingly successful against many systemic tumors, clinical efficacy against brain tumors has been limited. One reason for this is an incomplete understanding of the local immunologic tumor microenvironment, particularly the function of large numbers of infiltrating myeloid derived cells. Monocytes/microglia are myeloid derived immunomodulatory cells, and they represent the predominant infiltrating immune cell population in gliomas. Our group has previously demonstrated using complementary in vitro and in vivo approaches that GBM tumor cells polarize tumor-associated myeloid cells (TAMs) and suppress their immunostimulatory function. Methods and Results: To better understand the mechanisms responsible for this immunosuppression, we used gene expression profiling of stimulated monocytes in the presence or absence of GBM tumor cells. Our analysis identified caveolin-1 (CAV1), a plasma membrane molecule with pleiotropic functions, as significantly up-regulated in monocytes in the presence of GBMs. We validated these findings ex vivo by confirming up-regulation of CAV1 in TAMs isolated from GBMs immediately after surgical resection. Finally, we demonstrate that siRNA inhibition of CAV1 restores myeloid cell function, as measured by TNF-alpha secretion, in the presence of GBMs. Conclusions: Restoration of TAM function through pharmacologic blockage of CAV1 may facilitate more successful immunotherapeutic strategies directed against a variety of solid human tumors infiltrated by TAMs

The role of the pathologist in tissue banking: European Consensus Expert Group Report

Human tissue biobanking encompasses a wide range of activities and study designs and is critical for application of a wide range of new technologies (-“omics”) to the discovery of molecular patterns of disease and for implementation of novel biomarkers into clinical trials. Pathology is the cornerstone of hospital-based tissue biobanking. Pathologists not only provide essential information identifying the specimen but also make decisions on what should be biobanked, making sure that the timing of all operations is consistent with both the requirements of clinical diagnosis and the optimal preservation of biological products. This document summarizes the conclusions of a Pathology Expert Group Meeting within the European Biological and Biomolecular Research Infrastructure (BBMRI) Program. These recommendations are aimed at providing guidance for pathologists as well as for institutions hosting biobanks on how to better integrate and support pathological activities within the framework of biobanks that fulfill international standards

Parametric POMDPs for planning in continuous state spaces

This thesis is concerned with planning and acting under uncertainty in partially-observable continuous domains. In particular, it focusses on the problem of mobile robot navigation given a known map. The dominant paradigm for robot localisation is to use Bayesian estimation to maintain a probability distribution over possible robot poses. In contrast, control algorithms often base their decisions on the assumption that a single state, such as the mode of this distribution, is correct. In scenarios involving significant uncertainty, this can lead to serious control errors. It is generally agreed that the reliability of navigation in uncertain environments would be greatly improved by the ability to consider the entire distribution when acting, rather than the single most likely state. The framework adopted in this thesis for modelling navigation problems mathematically is the Partially Observable Markov Decision Process (POMDP). An exact solution to a POMDP problem provides the optimal balance between reward-seeking behaviour and information-seeking behaviour, in the presence of sensor and actuation noise. Unfortunately, previous exact and approximate solution methods have had difficulty scaling to real applications. The contribution of this thesis is the formulation of an approach to planning in the space of continuous parameterised approximations to probability distributions. Theoretical and practical results are presented which show that, when compared with similar methods from the literature, this approach is capable of scaling to larger and more realistic problems. In order to apply the solution algorithm to real-world problems, a number of novel improvements are proposed. Specifically, Monte Carlo methods are employed to estimate distributions over future parameterised beliefs, improving planning accuracy without a loss of efficiency. Conditional independence assumptions are exploited to simplify the problem, reducing computational requirements. Scalability is further increased by focussing computation on likely beliefs, using metric indexing structures for efficient function approximation. Local online planning is incorporated to assist global offline planning, allowing the precision of the latter to be decreased without adversely affecting solution quality. Finally, the algorithm is implemented and demonstrated during real-time control of a mobile robot in a challenging navigation task. We argue that this task is substantially more challenging and realistic than previous problems to which POMDP solution methods have been applied. Results show that POMDP planning, which considers the evolution of the entire probability distribution over robot poses, produces significantly more robust behaviour when compared with a heuristic planner which considers only the most likely states and outcomes

High quality copy number and genotype data from FFPE samples using Molecular Inversion Probe (MIP) microarrays

BACKGROUND:A major challenge facing DNA copy number (CN) studies of tumors is that most banked samples with extensive clinical follow-up information are Formalin-Fixed Paraffin Embedded (FFPE). DNA from FFPE samples generally underperforms or suffers high failure rates compared to fresh frozen samples because of DNA degradation and cross-linking during FFPE fixation and processing. As FFPE protocols may vary widely between labs and samples may be stored for decades at room temperature, an ideal FFPE CN technology should work on diverse sample sets. Molecular Inversion Probe (MIP) technology has been applied successfully to obtain high quality CN and genotype data from cell line and frozen tumor DNA. Since the MIP probes require only a small (~40 bp) target binding site, we reasoned they may be well suited to assess degraded FFPE DNA. We assessed CN with a MIP panel of 50,000 markers in 93 FFPE tumor samples from 7 diverse collections. For 38 FFPE samples from three collections we were also able to asses CN in matched fresh frozen tumor tissue.RESULTS:Using an input of 37 ng genomic DNA, we generated high quality CN data with MIP technology in 88% of FFPE samples from seven diverse collections. When matched fresh frozen tissue was available, the performance of FFPE DNA was comparable to that of DNA obtained from matched frozen tumor (genotype concordance averaged 99.9%), with only a modest loss in performance in FFPE.CONCLUSION:MIP technology can be used to generate high quality CN and genotype data in FFPE as well as fresh frozen samples.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]