53 resultados para Peter W. Williams


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Aims: The utility of p53 as a prognostic assay has been elusive. The aims of this study were to describe a novel, reproducible scoring system and assess the relationship between differential p53 immunohistochemistry (IHC) expression patterns, TP53 mutation status and patient outcomes in breast cancer.

Methods and Results: Tissue microarrays were used to study p53 IHC expression patterns: expression was defined as extreme positive (EP), extreme negative (EN), and non-extreme (NE; intermediate patterns). Overall survival (OS) was used to define patient outcome. A representative subgroup (n = 30) showing the various p53 immunophenotypes was analysed for TP53 hotspot mutation status (exons 4-9). Extreme expression of any type occurred in 176 of 288 (61%) cases. As compared with NE expression, EP expression was significantly associated (P = 0.039) with poorer OS. In addition, as compared with NE expression, EN expression was associated (P = 0.059) with poorer OS. Combining cases showing either EP or EN expression better predicted OS than either pattern alone (P = 0.028). This combination immunophenotype was significant in univariate but not multivariate analysis. In subgroup analysis, six substitution exon mutations were detected, all corresponding to extreme IHC phenotypes. Five missense mutations corresponded to EP staining, and the nonsense mutation corresponded to EN staining. No mutations were detected in the NE group.

Conclusions: Patients with extreme p53 IHC expression have a worse OS than those with NE expression. Accounting for EN as well as EP expression improves the prognostic impact. Extreme expression positively correlates with nodal stage and histological grade, and negatively with hormone receptor status. Extreme expression may relate to specific mutational status.

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Molecular Pathology (MP) is at the heart of modern diagnostics and translational research, but the controversy on how MP is best developed has not abated. The lack of a proper model or trained pathologists to support the diagnostic and research missions makes MP a rare commodity overall. Here we analyse the scientific and technology areas, in research and diagnostics, which are encompassed by MP of solid tumours; we highlight the broad overlap of technologies and analytical capabilities in tissue research and diagnostics; and we describe an integrated model that rationalizes technical know-how and pathology talent for both. The model is based on a single, accredited laboratory providing a single standard of high-quality for biomarker discovery, biomarker validation and molecular diagnostics.

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Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

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Despite the increasing availability of digital slide viewing, and numerous advantages associated with its application, a lack of quality validation studies is amongst the reasons for poor uptake in routine practice. This study evaluated primary digital pathology reporting in the setting of routine subspecialist gastrointestinal pathology, commonplace in most tissue pathology laboratories and representing one of the highest volume specialties in most laboratories. Individual digital and glass slide diagnoses were compared amongst three pathologists reporting in a gastrointestinal subspecialty team, in a prospective series of 100 consecutive diagnostic cases from routine practice in a large teaching hospital laboratory. The study included a washout period of at least 6 months. Discordant diagnoses were classified, and the study evaluated against recent College of American Pathologists (CAP) recommendations for evaluating digital pathology systems for diagnostic use. The study design met all 12 of the CAP recommendations. The 100 study cases generated 300 pairs of diagnoses, comprising 100 glass slide diagnoses and 100 digital diagnoses from each of the three study pathologists. 286 of 300 pairs of diagnoses were concordant, representing intraobserver concordance of 95.3 %, broadly comparable to rates previously published in this field. In ten of the 14 discordant pairs, the glass slide diagnosis was favoured; in four cases, the digital diagnosis was favoured, but importantly, the 14 discordant intraobserver diagnoses were considered to be of minor clinical significance. Interobserver, or viewing modality independent, concordance was found in 94 of the total of 100 study cases, providing a comparable baseline discordance rate expected in any second viewing of pathology material. These overall results support the safe use of digital pathology in primary diagnostic reporting in this setting

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Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

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OBJECTIVES: The International Cancer Benchmarking Partnership (ICBP) is a collaboration between 6 countries and 12 jurisdictions with similar primary care-led health services. This study investigates primary care physician (PCP) behaviour and systems that may contribute to the timeliness of investigating for cancer and subsequently, international survival differences.

DESIGN: A validated survey administered to PCPs via the internet set out in two parts: direct questions on primary care structure and practice relating to cancer diagnosis, and clinical vignettes, assessing management of scenarios relating to the diagnosis of lung, colorectal or ovarian cancer.

PARTICIPANTS: 2795 PCPs in 11 jurisdictions: New South Wales and Victoria (Australia), British Columbia, Manitoba, Ontario (Canada), England, Northern Ireland, Wales (UK), Denmark, Norway and Sweden.

PRIMARY AND SECONDARY OUTCOME MEASURES: Analysis compared the cumulative proportion of PCPs in each jurisdiction opting to investigate or refer at each phase for each vignette with 1-year survival, and conditional 5-year survival rates for the relevant cancer and jurisdiction. Logistic regression was used to explore whether PCP characteristics or system differences in each jurisdiction affected the readiness to investigate.

RESULTS: 4 of 5 vignettes showed a statistically significant correlation (p<0.05 or better) between readiness to investigate or refer to secondary care at the first phase of each vignette and cancer survival rates for that jurisdiction. No consistent associations were found between readiness to investigate and selected PCP demographics, practice or health system variables.

CONCLUSIONS: We demonstrate a correlation between the readiness of PCPs to investigate symptoms indicative of cancer and cancer survival rates, one of the first possible explanations for the variation in cancer survival between ICBP countries. No specific health system features consistently explained these findings. Some jurisdictions may consider lowering thresholds for PCPs to investigate for cancer-either directly, or by specialist referral, to improve outcomes.

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The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics.

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Background: Although Plasmodium falciparum transmission frequently exhibits seasonal patterns, the drivers of malaria seasonality are often unclear. Given the massive variation in the landscape upon which transmission acts, intra-annual fluctuations are likely influenced by different factors in different settings. Further, the presence of potentially substantial inter-annual variation can mask seasonal patterns; it may be that a location has "strongly seasonal" transmission and yet no single season ever matches the mean, or synoptic, curve. Accurate accounting of seasonality can inform efficient malaria control and treatment strategies. In spite of the demonstrable importance of accurately capturing the seasonality of malaria, data required to describe these patterns is not universally accessible and as such localized and regional efforts at quantifying malaria seasonality are disjointed and not easily generalized. 

Methods: The purpose of this review was to audit the literature on seasonality of P. falciparum and quantitatively summarize the collective findings. Six search terms were selected to systematically compile a list of papers relevant to the seasonality of P. falciparum transmission, and a questionnaire was developed to catalogue the manuscripts. 

Results and discussion: 152 manuscripts were identified as relating to the seasonality of malaria transmission, deaths due to malaria or the population dynamics of mosquito vectors of malaria. Among these, there were 126 statistical analyses and 31 mechanistic analyses (some manuscripts did both). 

Discussion: Identified relationships between temporal patterns in malaria and climatological drivers of malaria varied greatly across the globe, with different drivers appearing important in different locations. Although commonly studied drivers of malaria such as temperature and rainfall were often found to significantly influence transmission, the lags between a weather event and a resulting change in malaria transmission also varied greatly by location. 

Conclusions: The contradicting results of studies using similar data and modelling approaches from similar locations as well as the confounding nature of climatological covariates underlines the importance of a multi-faceted modelling approach that attempts to capture seasonal patterns at both small and large spatial scales.

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The last 20 years have seen significant advances in cancer care in Northern Ireland, leading to measureable improvements in patient outcomes. Crucial to this transformation has been an ethos that recognizes the primacy role of research in effecting heath care change. The authors' model of a cross-sectoral partnership that unites patients, scientists, health care professionals, hospital trusts, bioindustry, and government agencies can be truly transformative, empowering tripartite clinical-academic-industry efforts that have already yielded significant benefit and will continue to inform strategy and its implementation going forward.

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Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use. Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling. Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman -0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively). By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.

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The treatment of cancer is becoming more precise, targeting specific oncogenic drivers with targeted molecular therapies. The epidermal growth factor receptor has been found to be over-expressed in a multitude of solid tumours. Immunohistochemistry is widely used in the fields of diagnostic and personalised medicine to localise and visualise disease specific proteins. To date the clinical utility of epidermal growth factor receptor immunohistochemistry in determining monoclonal antibody efficacy has remained somewhat inconclusive. The lack of an agreed reproducible scoring criteria for epidermal growth factor receptor immunohistochemistry has, in various clinical trials yielded conflicting results as to the use of epidermal growth factor receptor immunohistochemistry assay as a companion diagnostic. This has resulted in this test being removed from the licence for the drug panitumumab and not performed in clinical practice for cetuximab. In this review we explore the reasons behind this with a particular emphasis on colorectal cancer, and to suggest a way of resolving the situation through improving the precision of epidermal growth factor receptor immunohistochemistry with quantitative image analysis of digitised images complemented with companion molecular morphological techniques such as in situ hybridisation and section based gene mutation analysis.

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Purpose:
A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer (CRC) with potential diagnostic utility, culminating in publication of a CRC Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal-derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled.

Experimental Design:
We performed multi-region tissue RNA extraction/transcriptomic analysis using Colorectal Specific Arrays on invasive front, central tumor and lymph node regions selected from tissue samples from 25 CRC patients.

Results:
We identified a consensus 30 gene list which represents the intratumoral heterogeneity within a cohort of primary CRC tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential (HR=2.914 (CI 0.9286-9.162) in stage II/III CRC patients, but in addition we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread Epithelial Mesenchymal Transition (EMT). Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analysed.

Conclusions:
Gene expression profiles derived from the non-malignant stromal region can influence assignment of CRC transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision-making in CRC.

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Repositories containing high quality human biospecimens linked with robust and relevant clinical and pathological information are required for the discovery and validation of biomarkers for disease diagnosis, progression and response to treatment. Current molecular based discovery projects using either low or high throughput technologies rely heavily on ready access to such sample collections. It is imperative that modern biobanks align with molecular diagnostic pathology practices not only to provide the type of samples needed for discovery projects but also to ensure requirements for ongoing sample collections and the future needs of researchers are adequately addressed. Biobanks within comprehensive molecular pathology programmes are perfectly positioned to offer more than just tumour derived biospecimens; for example, they have the ability to facilitate researchers gaining access to sample metadata such as digitised scans of tissue samples annotated prior to macrodissection for molecular diagnostics or pseudoanonymised clinical outcome data or research results retrieved from other users utilising the same or overlapping cohorts of samples. Furthermore, biobanks can work with molecular diagnostic laboratories to develop standardized methodologies for the acquisition and storage of samples required for new approaches to research such as ‘liquid biopsies’ which will ultimately feed into the test validations required in large prospective clinical studies in order to implement liquid biopsy approaches for routine clinical practice. We draw on our experience in Northern Ireland to discuss how this harmonised approach of biobanks working synergistically with molecular pathology programmes is key for the future success of precision medicine.