214 research outputs found
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Somatic cancer genetics in the UK: real-world data from phase I of the Cancer Research UK Stratified Medicine Programme
Introduction
Phase I of the Cancer Research UK Stratified Medicine Programme (SMP1) was designed to roll out molecular pathology testing nationwide at the point of cancer diagnosis, as well as facilitate an infrastructure where surplus cancer tissue could be used for research. It offered a non-trial setting to examine common UK cancer genetics in a real-world context.
Methods
A total of 26 sites in England, Wales and Scotland, recruiting samples from 7,814 patients for genetic examination between 2011-2013. Tumor types involved were breast, colorectal, lung, prostate, ovary cancer and malignant melanoma. Centralised molecular testing of surplus material from resections or biopsies of primary/metastatic tissue was performed, with samples examined for 3-5 genetic alterations deemed to be of key interest in site-specific cancers by National Cancer Research Institute Clinical Study groups.
Results
10,754 patients (98% of those approached) consented to participate, from which 7,814 tumor samples were genetically analysed. In total, 53% had at least one genetic aberration detected. From 1885 lung cancer patients, KRAS mutation was noted to be highly prevalent in adenocarcinoma (37%). In breast cancer (1873 patients), there was a striking contrast in TP53 mutation incidence between patients with ductal cancer (27.3%) and lobular cancer (3.4%). Vast inter-tumor heterogeneity of colorectal cancer (1550 patients) was observed , including myriad double and triple combinations of genetic aberrations. Significant losses of important clinical information included smoking status in lung cancer and loss of distinction between low and high grade serous ovarian cancers.
Conclusion
Nationwide molecular pathology testing in a non-trial setting is feasible. The experience with SMP1 has been used to inform ongoing CRUK flagship programmes such as the CRUK National Lung MATRIX trial and TRACERx.Funding for the Stratified Medicine Programme is acknowledged from Cancer Research UK and programme founding partners AstraZeneca and Pfizer. For hosting the Stratified Medicine Programme data, thanks to the National Cancer Registration Service Eastern Office, Jim Davies and Steve Harris at the University of Oxford Department of Computer Science. AGN was supported by the National Institute of Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College London. PJ, ES and CL have all been employed by Cancer Research UK in the past. FB was supported by Cancer Research UK Lung Cancer Centre of Excellence Funding. WAW was supported by Lothian NRS BioResource. SP acknowledges NHS funding to the NIHR Biomedical Research Centre at The Royal Marsden and the ICR. NPW is supported by Yorkshire Cancer Research. KGB is supported by a NHS Research Scotland Senior Fellowship
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Exploratory Analysis of Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study
Circulating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP).
We performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP. The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%-22%) compared to 0.7% (IQR 0.3%-2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson = 0.59, 32 cm, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28-54) compared with a median time to nadir of 84 d (IQR 42-116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07-0.67, = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%-92%) and 88% specificity (95% CI 64%-99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort.
In this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.This work was supported by Cancer Research UK Grant numbers: A15601 (JDB), A11906 (NR), A20240 (NR), A18072 (JDB). JDB was supported by the National Institute for Health Research Cambridge Biomedical Research Centre. CAP was supported in part by the Academy of Medical Sciences, the Wellcome Trust, British Heart Foundation and Arthritis Research UK
International Agency for Research on Cancer Workshop on 'Expression array analyses in breast cancer taxonomy'
In May 2006, a workshop on Expression array analyses in breast cancer taxonomy was held at the International Agency for Research on Cancer (IARC). The workshop covered an array of topics from the validity of the currently defined breast tumor subtypes and other expression profile-based signatures to the technical limitations of expression analysis and the types of platforms on which these omics results will eventually reach clinical practice. Overall, the workshop participants believed firmly that tumor taxonomy is likely to yield improved prognostic and predictive markers. Even so, further standardization and validation are required before clinical trials are set in motion
High-throughput genomic technology in research and clinical management of breast cancer. Molecular signatures of progression from benign epithelium to metastatic breast cancer
It is generally accepted that early detection of breast cancer has great impact on patient survival, emphasizing the importance of early diagnosis. In a widely recognized model of breast cancer development, tumor cells progress through chronological and well defined stages. However, the molecular basis of disease progression in breast cancer remains poorly understood. High-throughput molecular profiling techniques are excellent tools for the study of complex molecular alterations. By accurately mapping changes in the genome and subsequent biological/molecular pathways, the chances of finding potential novel treatment targets as well as intervention strategies are enhanced, and ultimately lives can be saved. This review provides a brief summary of recent progress in identifying molecular markers for invasiveness in early breast lesions
Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer
The widespread introduction of high throughput RNA interference screening technology has revealed tumour drug sensitivity pathways to common cytotoxics such as paclitaxel, doxorubicin and 5-fluorouracil, targeted agents such as trastuzumab and inhibitors of AKT and Poly(ADP-ribose) polymerase (PARP) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts
Clinicopathological, therapeutic and prognostic features of the triple-negative tumors in moroccan breast cancer patients (experience of Hassan II university hospital in Fez)
<p>Abstract</p> <p>Introduction</p> <p>Triple-negative breast cancer (TNBC) is defined as a group of breast carcinomas that are negative for expression of hormone receptors (ER, PR) and Her2, we can distinguish between two groups: basal-like (ER-, PR-, Her2-, cytokeratin (CK) 5/6+ and/or Her1+) and unclassified subtype (ER-, PR-, Her2-, Her1- and CK5/6-).</p> <p>The aim of this study is to determine the clinicopathological, histological, therapeutic and prognostic features associated with this type of breast cancer.</p> <p>Methods</p> <p>This is a retrospective study of 366 female breast cancer patients, diagnosed between January 2007 and June 2010 at the Department of Pathology. Epidemiological, clinical, histological, therapeutic and evolutive data were analyzed. OS and DFS rates were estimated by Kaplan-Meier analysis and a log-rank test to estimate outcome.</p> <p>Results</p> <p>A total of 64 women were identified as having TNBC (17.5% of all female breast cancer patients), 12.6% were basal-like, 4.9% were unclassified subtype, with a median age of 45 years. The median histological tumor diameter was 4.3 cm. TNBC were most often associated with a high grade, 49.2% grade III (53% for unclassified subtype, 47.6% for basal-like). Vascular invasion was found in 26.6% of cases (22% for unclassified subtype and 28.3% for basal-like). For the lymph node involvement: 51% had positive lymph nodes, and 22.4% had distant metastases. Neoadjuvant chemotherapy was administered to 18% patients with 26% of complete pathologic response; therefore adjuvant chemotherapy was given to 82%. 98% received anthracycline based regimen and only 30% received taxanes.</p> <p>The Kaplan-Meier curves based showed the lowest survival probability at 3-years (49% of OS, and 39% of DFS).</p> <p>Conclusion</p> <p>TNBC is associated with young age, high grade tumors, advanced stage at diagnosis, difference chemo response compared to other subtypes, and shortest survival. Critical to optimal future management is accurate identification of truly triple negative disease, and adequately powered prospective TNBC trials to establish treatment efficacy and define predictive biomarkers.</p
A prospective observational study to assess the diagnostic accuracy of clinical decision rules for children presenting to emergency departments after head injuries (protocol): The Australasian Paediatric Head Injury Rules Study (APHIRST)
Background: Head injuries in children are responsible for a large number of emergency department visits. Failure to identify a clinically significant intracranial injury in a timely fashion may result in long term neurodisability and death. Whilst cranial computed tomography (CT) provides rapid and definitive identification of intracranial injuries, it is resource intensive and associated with radiation induced cancer. Evidence based head injury clinical decision rules have been derived to aid physicians in identifying patients at risk of having a clinically significant intracranial injury. Three rules have been identified as being of high quality and accuracy: the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) from Canada, the Children's Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) from the UK, and the prediction rule for the identification of children at very low risk of clinically important traumatic brain injury developed by the Pediatric Emergency Care Applied Research Network (PECARN) from the USA. This study aims to prospectively validate and compare the performance accuracy of these three clinical decision rules when applied outside the derivation setting.Methods/design: This study is a prospective observational study of children aged 0 to less than 18 years presenting to 10 emergency departments within the Paediatric Research in Emergency Departments International Collaborative (PREDICT) research network in Australia and New Zealand after head injuries of any severity. Predictor variables identified in CATCH, CHALICE and PECARN clinical decision rules will be collected. Patients will be managed as per the treating clinicians at the participating hospitals. All patients not undergoing cranial CT will receive a follow up call 14 to 90 days after the injury. Outcome data collected will include results of cranial CTs (if performed) and details of admission, intubation, neurosurgery and death. The performance accuracy of each of the rules will be assessed using rule specific outcomes and inclusion and exclusion criteria.Discussion: This study will allow the simultaneous comparative application and validation of three major paediatric head injury clinical decision rules outside their derivation setting.Trial registration: The study is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR)- ACTRN12614000463673 (registered 2 May 2014). © 2014 Babl et al.; licensee BioMed Central Ltd
Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients
BACKGROUND: Molecular markers and the rich biological information they contain have great potential for cancer diagnosis, prognostication and therapy prediction. So far, however, they have not superseded routine histopathology and staging criteria, partly because the few studies performed on molecular subtyping have had little validation and limited clinical characterization. METHODS: We obtained gene expression and clinical data for 412 breast cancers obtained from population-based cohorts of patients from Stockholm and Uppsala, Sweden. Using the intrinsic set of approximately 500 genes derived in the Norway/Stanford breast cancer data, we validated the existence of five molecular subtypes – basal-like, ERBB2, luminal A/B and normal-like – and characterized these subtypes extensively with the use of conventional clinical variables. RESULTS: We found an overall 77.5% concordance between the centroid prediction of the Swedish cohort by using the Norway/Stanford signature and the k-means clustering performed internally within the Swedish cohort. The highest rate of discordant assignments occurred between the luminal A and luminal B subtypes and between the luminal B and ERBB2 subtypes. The subtypes varied significantly in terms of grade (p < 0.001), p53 mutation (p < 0.001) and genomic instability (p = 0.01), but surprisingly there was little difference in lymph-node metastasis (p = 0.31). Furthermore, current users of hormone-replacement therapy were strikingly over-represented in the normal-like subgroup (p < 0.001). Separate analyses of the patients who received endocrine therapy and those who did not receive any adjuvant therapy supported the previous hypothesis that the basal-like subtype responded to adjuvant treatment, whereas the ERBB2 and luminal B subtypes were poor responders. CONCLUSION: We found that the intrinsic molecular subtypes of breast cancer are broadly present in a diverse collection of patients from a population-based cohort in Sweden. The intrinsic gene set, originally selected to reveal stable tumor characteristics, was shown to have a strong correlation with progression-related properties such as grade, p53 mutation and genomic instability
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