PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-8 (8)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
1.  Development and implementation of a custom integrated database with dashboards to assist with hematopathology specimen triage and traffic 
Background:
At some institutions, including ours, bone marrow aspirate specimen triage is complex, with hematopathology triage decisions that need to be communicated to downstream ancillary testing laboratories and many specimen aliquot transfers that are handled outside of the laboratory information system (LIS). We developed a custom integrated database with dashboards to facilitate and streamline this workflow.
Methods:
We developed user-specific dashboards that allow entry of specimen information by technologists in the hematology laboratory, have custom scripting to present relevant information for the hematopathology service and ancillary laboratories and allow communication of triage decisions from the hematopathology service to other laboratories. These dashboards are web-accessible on the local intranet and accessible from behind the hospital firewall on a computer or tablet. Secure user access and group rights ensure that relevant users can edit or access appropriate records.
Results:
After database and dashboard design, two-stage beta-testing and user education was performed, with the first focusing on technologist specimen entry and the second on downstream users. Commonly encountered issues and user functionality requests were resolved with database and dashboard redesign. Final implementation occurred within 6 months of initial design; users report improved triage efficiency and reduced need for interlaboratory communications.
Conclusions:
We successfully developed and implemented a custom database with dashboards that facilitates and streamlines our hematopathology bone marrow aspirate triage. This provides an example of a possible solution to specimen communications and traffic that are outside the purview of a standard LIS.
doi:10.4103/2153-3539.139709
PMCID: PMC4168549  PMID: 25250187
Custom informatics; custom laboratory database; dashboard; hematopathology; pathology informatics
2.  Association Between a Germline OCA2 Polymorphism at Chromosome 15q13.1 and Estrogen Receptor–Negative Breast Cancer Survival 
Background
Traditional prognostic factors for survival and treatment response of patients with breast cancer do not fully account for observed survival variation. We used available genotype data from a previously conducted two-stage, breast cancer susceptibility genome-wide association study (ie, Studies of Epidemiology and Risk factors in Cancer Heredity [SEARCH]) to investigate associations between variation in germline DNA and overall survival.
Methods
We evaluated possible associations between overall survival after a breast cancer diagnosis and 10 621 germline single-nucleotide polymorphisms (SNPs) from up to 3761 patients with invasive breast cancer (including 647 deaths and 26 978 person-years at risk) that were genotyped previously in the SEARCH study with high-density oligonucleotide microarrays (ie, hypothesis-generating set). Associations with all-cause mortality were assessed for each SNP by use of Cox regression analysis, generating a per rare allele hazard ratio (HR). To validate putative associations, we used patient genotype information that had been obtained with 5′ nuclease assay or mass spectrometry and overall survival information for up to 14 096 patients with invasive breast cancer (including 2303 deaths and 70 019 person-years at risk) from 15 international case–control studies (ie, validation set). Fixed-effects meta-analysis was used to generate an overall effect estimate in the validation dataset and in combined SEARCH and validation datasets. All statistical tests were two-sided.
Results
In the hypothesis-generating dataset, SNP rs4778137 (C>G) of the OCA2 gene at 15q13.1 was statistically significantly associated with overall survival among patients with estrogen receptor–negative tumors, with the rare G allele being associated with increased overall survival (HR of death per rare allele carried = 0.56, 95% confidence interval [CI] = 0.41 to 0.75, P = 9.2 × 10−5). This association was also observed in the validation dataset (HR of death per rare allele carried = 0.88, 95% CI = 0.78 to 0.99, P = .03) and in the combined dataset (HR of death per rare allele carried = 0.82, 95% CI = 0.73 to 0.92, P = 5 × 10−4).
Conclusion
The rare G allele of the OCA2 polymorphism, rs4778137, may be associated with improved overall survival among patients with estrogen receptor–negative breast cancer.
doi:10.1093/jnci/djq057
PMCID: PMC2864289  PMID: 20308648
3.  A genome-wide association study of prognosis in breast cancer 
Background
Traditional clinicopathological features of breast cancer do not account for all the variation in survival. Germline genetic variation may provide additional prognostic information.
Materials and Methods
We conducted a GWAS study of survival after a diagnosis of breast cancer by obtaining follow-up data and genotyping information on 528,252 SNPs for 1,145 postmenopausal women with invasive breast cancer (7,711 person years at risk) from the Nurses’ Health Study scanned in the Cancer Genetic Markers of Susceptibility initiative. We genotyped the ten most statistically significant loci (most significant SNP located in ARHGAP10, p = 2.28 × 10−7) in 4,335 women diagnosed with invasive breast cancer (38,148 years at risk) in the SEARCH breast cancer study.
Results
None of the loci replicated in the SEARCH study (all p > 0.10). Assuming a minimum of ten associated loci, the power to detect at least one with a minor allele frequency of 0.2 conferring a relative hazard of 2.0 at genome-wide significance (5×10−8) was 99 percent.
Conclusions
We did not identify any common germline variants associated with breast cancer survival overall.
Impact
Our data suggest it is unlikely that there are common germline variants with large effect sizes for breast cancer survival overall (HR>2). Instead, it is plausible that common variants associated with survival could be specific to tumor subtypes or treatment approaches. New studies, sufficiently powered, are needed to discover new regions associated with survival overall or by subtype or treatment subgroups.
doi:10.1158/1055-9965.EPI-10-0085
PMCID: PMC2852476  PMID: 20332263
breast cancer; prognosis; genome-wide association study; molecular diagnosis and prognosis; single nucleotide polymorphism
4.  Genome-Wide Meta-Analysis Identifies Regions on 7p21 (AHR) and 15q24 (CYP1A2) As Determinants of Habitual Caffeine Consumption 
PLoS Genetics  2011;7(4):e1002033.
We report the first genome-wide association study of habitual caffeine intake. We included 47,341 individuals of European descent based on five population-based studies within the United States. In a meta-analysis adjusted for age, sex, smoking, and eigenvectors of population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4×10−19), near AHR, and 15q24 (P = 5.2×10−14), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.
Author Summary
Caffeine is the most widely consumed psychoactive substance in the world. Although demographic and social factors have been linked to habitual caffeine consumption, twin studies report a large heritable component. Through a comprehensive search of the human genome involving over 40,000 participants, we discovered two loci associated with habitual caffeine consumption: the first near AHR and the second between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates, as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2. Caffeine intake has been associated with manifold physiologic effects and both detrimental and beneficial health outcomes. Knowledge of the genetic determinants of caffeine intake may provide insight into underlying mechanisms and may provide ways to study the potential health effects of caffeine more comprehensively.
doi:10.1371/journal.pgen.1002033
PMCID: PMC3071630  PMID: 21490707
6.  PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer 
Introduction
The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK.
Methods
Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation.
Results
Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75).
Conclusions
We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.
doi:10.1186/bcr2464
PMCID: PMC2880419  PMID: 20053270
7.  SLC6A3 and body mass index in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial 
BMC Medical Genetics  2009;10:9.
Background
To investigate the contribution of the dopamine transporter to dopaminergic reward-related behaviors and anthropometry, we evaluated associations between polymorphisms at the dopamine transporter gene(SLC6A3) and body mass index (BMI), among participants in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.
Methods
Four polymorphisms (rs6350, rs6413429, rs6347 and the 3' variable number of tandem repeat (3' VNTR) polymorphism) at the SLC6A3 gene were genotyped in 2,364 participants selected from the screening arm of PLCO randomly within strata of sex, age and smoking history. Height and weight at ages 20 and 50 years and baseline were assessed by questionnaire. BMI was calculated and categorized as underweight, normal, overweight and obese (<18.5, 18.5–24.9, 25.0–29.9, or ≥ 30 kg/m2, respectively). Odds ratios (ORs) and 95% confidence intervals (CIs) of SLC6A3 genotypes and haplotypes were computed using conditional logistic regression.
Results
Compared with individuals having a normal BMI, obese individuals at the time of the baseline study questionnaire were less likely to possess the 3' VNTR variant allele with 9 copies of the repeated sequence in a dose-dependent model (** is referent; OR*9 = 0.80, OR99 = 0.47, ptrend = 0.005). Compared with individuals having a normal BMI at age 50, overweight individuals (A-C-G-* is referent; ORA-C-G-9 = 0.80, 95% CI 0.65–0.99, p = 0.04) and obese individuals (A-C-G-* is referent; ORA-C-G-9 = 0.70, 95% CI 0.49–0.99, p = 0.04) were less likely to possess the haplotype with the 3'variant allele (A-C-G-9).
Conclusion
Our results support a role of genetic variation at the dopamine transporter gene, SLC6A3, as a modifier of BMI.
doi:10.1186/1471-2350-10-9
PMCID: PMC2640369  PMID: 19183461
8.  Effects of common germline genetic variation in cell cycle control genes on breast cancer survival: results from a population-based cohort 
Introduction
Somatic alterations have been shown to correlate with breast cancer prognosis and survival, but less is known about the effects of common inherited genetic variation. Of particular interest are genes involved in cell cycle pathways, which regulate cell division.
Methods
We examined associations between common germline genetic variation in 13 genes involved in cell cycle control (CCND1, CCND2, CCND3, CCNE1, CDK2 [p33], CDK4, CDK6, CDKN1A [p21, Cip1], CDKN1B [p27, Kip1], CDKN2A [p16], CDKN2B [p15], CDKN2C [p18], and CDKN2D [p19]) and survival among women diagnosed with invasive breast cancer participating in the SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity) breast cancer study. DNA from up to 4,470 women was genotyped for 85 polymorphisms that tag the known common polymorphisms (minor allele frequency > 0.05) in the genes. The genotypes of each polymorphism were tested for association with survival using Cox regression analysis.
Results
The rare allele of the tagging single nucleotide polymorphism (SNP) rs2479717 is associated with an increased risk of death (hazard ratio = 1.26 per rare allele carried, 95% confidence interval: 1.12 to 1.42; P = 0.0001), which was not attenuated after adjusting for tumour stage, grade, and treatment. This SNP is part of a large linkage disequilibrium block, which contains CCND3, BYSL, TRFP, USP49, C6ofr49, FRS3, and PGC. We evaluated the association of survival and somatic expression of these genes in breast tumours using expression microarray data from seven published datasets. Elevated expression of the C6orf49 transcript was associated with breast cancer survival, adding biological interest to the finding.
Conclusion
It is possible that CCND3 rs2479717, or another variant it tags, is associated with prognosis after a diagnosis of breast cancer. Further study is required to validate this finding.
doi:10.1186/bcr2100
PMCID: PMC2481496  PMID: 18507837

Results 1-8 (8)