TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Beta-blocker usage and breast cancer survival: a nested case-control study within a UK clinical practice research datalink cohort.

Background: To investigate the association between post-diagnostic beta-blocker usage and risk of cancer-specific mortality in a large population-based cohort of female breast cancer patients.

Methods: A nested case-control study was conducted within a cohort of breast cancer patients identified from cancer registries in England(using the National Cancer Data repository) and diagnosed between 1998 and 2007. Patients who had a breast cancer-specific death(ascertained from Office of National Statistics death registration data) were each matched to four alive controls by year and age at diagnosis. Prescription data for these patients were available through the Clinical Practice Research Datalink. Conditional logistic regression models were used to investigate the association between breast cancer-specific death and beta-blocker usage.

Results: Post-diagnostic use of beta-blockers was identified in 18.9% of 1435 breast cancer-specific deaths and 19.4% of their 5697 matched controls,indicating little evidence of association between beta-blocker use and breast cancer-specific mortality [odds ratio (OR) = 0.97,95% confidence interval (CI) 0.83, 1.13]. There was also little evidence of an association when analyses were restricted to cardio non-selective beta-blockers (OR = 0.90, 95% CI 0.69, 1.17). Similar results were observed in analyses of drug dosage frequency and duration, and beta-blocker type.

Conclusions: In this large UK population-based cohort of breast cancer patients,there was little evidence of an association between post-diagnostic beta-blocker usage and breast cancer progression. Further studies which include information on tumour receptor status are warranted to determine whether response to beta-blockers varies by tumour subtypes.

Post-diagnostic oral bisphosphonate use and colorectal cancer mortality: a population-based cohort study within the UK Clinical Practice Research Datalink

Background:We conducted the first study to investigate post-diagnostic oral bisphosphonates use and colorectal cancer-specific mortality.

Methods:Colorectal cancer patients were identified from the National Cancer Data Repository (1998–2007) and linked to the UK Clinical Practice Research Datalink, providing prescription records, and Office of National Statistics mortality data. Time-dependent Cox regression models investigated colorectal cancer-specific mortality in post-diagnostic bisphosphonate users.

Results:Overall, in 4791 colorectal cancer patients, there was no evidence of an association between bisphosphonate use and colorectal cancer-specific mortality (adjusted hazard ratio=1.11; 95% confidence interval 0.80, 1.54) or with drug frequency or type.

Conclusions:In this novel population-based cohort study, post-diagnostic bisphosphonate use was not associated with longer rates of colorectal cancer survival.

Digoxin use after diagnosis of breast cancer and survival: a population-based cohort study

Digoxin has been shown to have an estrogenic effect and is associated with increased risk of gynecomastia and estrogen-sensitive cancers such as breast and uterus cancer. These findings, particularly recent observations of increased breast cancer risk, raise questions about the safety of digoxin use in breast cancer patients. Therefore, we investigated whether digoxin use after breast cancer diagnosis increased the risk of breast cancer-specific mortality in breast cancer patients. A cohort of 17,842 breast cancer patients newly diagnosed from 1998 to 2009 was identified from English cancer registries (from the National Cancer Data Repository). This cohort was linked to the UK Clinical Practice Research Datalink (to provide digoxin and other prescription records) and to the Office of National Statistics mortality data (to identify breast cancer-specific deaths). Using time-dependent Cox regression models, unadjusted and adjusted hazard ratios (HR) and 95 % confidence intervals (CIs) were calculated for the association between post-diagnostic exposure to digoxin and breast cancer-specific and all-cause mortality. In 17,842 breast cancer patients, there were 2219 breast cancer-specific deaths. Digoxin users appeared to have increased breast cancer-specific mortality compared with non-users (HR 1.73; 95 % CI 1.39–2.15) but this association was entirely attenuated after adjustment for potential confounders (adjusted HR 0.91; 95 % CI 0.72–1.14). In this large population-based breast cancer cohort study, there was little evidence of an increase in breast cancer-specific mortality with digoxin use after diagnosis. These results provide some reassurance that digoxin use is safe in breast cancer patients.

Statin use after colorectal cancer diagnosis and survival: a population-based cohort study

PURPOSE: To investigate whether statins used after colorectal cancer diagnosis reduce the risk of colorectal cancer-specific mortality in a cohort of patients with colorectal cancer.

PATIENTS AND METHODS: A cohort of 7,657 patients with newly diagnosed stage I to III colorectal cancer were identified from 1998 to 2009 from the National Cancer Data Repository (comprising English cancer registry data). This cohort was linked to the United Kingdom Clinical Practice Research Datalink, which provided prescription records, and to mortality data from the Office of National Statistics (up to 2012) to identify 1,647 colorectal cancer-specific deaths. Time-dependent Cox regression models were used to calculate hazard ratios (HR) for cancer-specific mortality and 95% CIs by postdiagnostic statin use and to adjust these HRs for potential confounders.

RESULTS: Overall, statin use after a diagnosis of colorectal cancer was associated with reduced colorectal cancer-specific mortality (fully adjusted HR, 0.71; 95% CI, 0.61 to 0.84). A dose-response association was apparent; for example, a more marked reduction was apparent in colorectal cancer patients using statins for more than 1 year (adjusted HR, 0.64; 95% CI, 0.53 to 0.79). A reduction in all-cause mortality was also apparent in statin users after colorectal cancer diagnosis (fully adjusted HR, 0.75; 95% CI, 0.66 to 0.84).

CONCLUSION: In this large population-based cohort, statin use after diagnosis of colorectal cancer was associated with longer rates of survival.

Low-dose aspirin and survival from lung cancer: a population-based cohort study

Background
Preclinical evidence suggests that aspirin may inhibit lung cancer progression. In a large cohort of lung cancer patients, we investigated whether low-dose aspirin use was associated with a reduction in the risk of lung cancer-specific mortality.

Methods
We identified lung cancer patients from English cancer registries diagnosed between 1998 to 2009 from the National Cancer Data Repository. Medication usage was obtained from linkages to the UK Clinical Practice Research Datalink and lung cancer-specific deaths were identified from Office of National Statistics mortality data. Hazard ratios (HR) and 95 % confidence intervals (CI) for the association between low-dose aspirin use (before and after diagnosis) and risk of lung cancer-specific mortality were calculated using Cox regression models.

Results
A total of 14,735 lung cancer patients were identified during the study period. In analysis of 3,635 lung cancer patients, there was no suggestion of an association between low-dose aspirin use after diagnosis and cancer-specific mortality (adjusted HR = 0.96, 95 % CI: 0.85, 1.09). Similarly, no association was evident for low-dose aspirin use before diagnosis and cancer-specific mortality (adjusted HR = 1.00, 95 % CI: 0.95, 1.05). Associations were comparable by duration of use and for all-cause mortality.

Conclusion
Overall, we found little evidence of a protective association between low-dose aspirin use and cancer-specific mortality in a large population-based lung cancer cohort.

Clopidogrel use and cancer-specific mortality: a population-based cohort study of colorectal, breast and prostate cancer patients

PURPOSE: Concerns were raised about the safety of antiplatelet thienopyridine derivatives after a randomized control trial reported increased risks of cancer and cancer deaths in prasugrel users. We investigate whether clopidogrel, a widely used thienopyridine derivative, was associated with increased risk of cancer-specific or all-cause mortality in cancer patients.

METHODS: Colorectal, breast and prostate cancer patients, newly diagnosed from 1998 to 2009, were identified from the National Cancer Data Repository. Cohorts were linked to the UK Clinical Practice Research Datalink, providing prescription records, and to the Office of National Statistics mortality data (up to 2012). Unadjusted and adjusted hazard ratios (HRs) for cancer-specific and all-cause mortality in post-diagnostic clopidogrel users were calculated using time-dependent Cox regression models.

RESULTS: The analysis included 10 359 colorectal, 17 889 breast and 13 155 prostate cancer patients. There was no evidence of an increase in cancer-specific mortality in clopidogrel users with colorectal (HR = 0.98 95% confidence interval (CI) 0.77, 1.24) or prostate cancer (HR = 1.03 95%CI 0.82, 1.28). There was limited evidence of an increase in breast cancer patients (HR = 1.22 95%CI 0.90, 1.65); however, this was attenuated when removing prescriptions in the year prior to death.

CONCLUSIONS: This novel study of large population-based cohorts of colorectal, breast and prostate cancer patients found no evidence of an increased risk of cancer-specific mortality among colorectal, breast and prostate cancer patients using clopidogrel.

Statin use after diagnosis of breast cancer and survival: a population-based cohort study

BACKGROUND: Preclinical studies have shown that statins, particularly simvastatin, can prevent growth in breast cancer cell lines and animal models. We investigated whether statins used after breast cancer diagnosis reduced the risk of breast cancer-specific, or all-cause, mortality in a large cohort of breast cancer patients.

METHODS: A cohort of 17,880 breast cancer patients, newly diagnosed between 1998 and 2009, was identified from English cancer registries (from the National Cancer Data Repository). This cohort was linked to the UK Clinical Practice Research Datalink, providing prescription records, and to the Office of National Statistics mortality data (up to 2013), identifying 3694 deaths, including 1469 deaths attributable to breast cancer. Unadjusted and adjusted hazard ratios (HRs) for breast cancer-specific, and all-cause, mortality in statin users after breast cancer diagnosis were calculated using time-dependent Cox regression models. Sensitivity analyses were conducted using multiple imputation methods, propensity score methods and a case-control approach.

RESULTS: There was some evidence that statin use after a diagnosis of breast cancer had reduced mortality due to breast cancer and all causes (fully adjusted HR = 0.84 [95% confidence interval = 0.68-1.04] and 0.84 [0.72-0.97], respectively). These associations were more marked for simvastatin 0.79 (0.63-1.00) and 0.81 (0.70-0.95), respectively.

CONCLUSIONS: In this large population-based breast cancer cohort, there was some evidence of reduced mortality in statin users after breast cancer diagnosis. However, these associations were weak in magnitude and were attenuated in some sensitivity analyses.

Applying the expanding photosphere and standardized candle methods to Type II-Plateau supernovae at cosmologically significant redshifts . The distance to SN 2013eq

Based on optical imaging and spectroscopy of the Type II-Plateau SN 2013eq, we present a comparative study of commonly used distance determination methods based on Type II supernovae. The occurrence of SN 2013eq in the Hubble flow (z = 0.041 ± 0.001) prompted us to investigate the implications of the difference between "angular" and "luminosity" distances within the framework of the expanding photosphere method (EPM) that relies upon a relation between flux and angular size to yield a distance. Following a re-derivation of the basic equations of the EPM for SNe at non-negligible redshifts, we conclude that the EPM results in an angular distance. The observed flux should be converted into the SN rest frame and the angular size, θ, has to be corrected by a factor of (1 + z)2. Alternatively, the EPM angular distance can be converted to a luminosity distance by implementing a modification of the angular size. For SN 2013eq, we find EPM luminosity distances of DL = 151 ± 18 Mpc and DL = 164 ± 20 Mpc by making use of different sets of dilution factors taken from the literature. Application of the standardized candle method for Type II-P SNe results in an independent luminosity distance estimate (DL = 168 ± 16 Mpc) that is consistent with the EPM estimate. Spectra of SN 2013eq are available in the Weizmann Interactive Supernova data REPository (WISeREP): http://wiserep.weizmann.ac.il

Bagging statistical network inference from large-scale gene expression data.

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

Building a 'Repository of Science': the importance of integrating Biobanks within molecular pathology programmes

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.