| 1. |
- Andersson, Kristin, et al.
(författare)
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The interface of population-based cancer registries and biobanks in etiological and clinical research : current and future perspectives
- 2010
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Ingår i: Acta Oncologica. - 0284-186X .- 1651-226X. ; 49:8, s. 1227-1234
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The availability of quality assured, population-based cancer registries and biobanks with high quality samples makes it possible to conduct research on large samples sets with long follow-up within a reasonable time frame. Defined quality for both cancer registries and biobanks is essential for enabling high quality biobank-based research. Recent networking projects have brought these infrastructures together to promote the combined use of cancer registries and biobanks in cancer research.MATERIALS AND METHODS: In this report we review the current status and future perspectives of cancer registries and biobanks and how the interface between them should be developed to optimally further cancer research.RESULTS AND DISCUSSION: Major conclusions for future improvements are that the research exploiting cancer registries and biobanks, and the research that is building and optimising the infrastructure, should evolve together for maximally relevant progress. Population-based and sustainable biobanks that continuously and consecutively store all samples ("Biological registries") under strict quality control are needed. There is also a need for increased education, information and visibility of the interdisciplinary sciences required for optimal exploitation of these resources.
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| 2. |
- Petrov, Dmitry, et al.
(författare)
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Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
- 2017
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Ingår i: Machine learning in medical imaging. MLMI (Workshop). - Cham : Springer International Publishing. ; 10541, s. 371-378
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Tidskriftsartikel (refereegranskat)abstract
- As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability.
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| 3. |
- Schmidt, Julie A, et al.
(författare)
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Insulin-like growth factor-I and risk of differentiated thyroid carcinoma in the European Prospective Investigation into Cancer and Nutrition
- 2014
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 23:6, s. 976-985
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Tidskriftsartikel (refereegranskat)abstract
- Background: Little is known about the causes of thyroid cancer, but insulin-like growth factor-I (IGF-I) might play an important role in its development due to its mitogenic and anti-apoptotic properties. Methods: This study prospectively investigated the association between serum IGF-I concentrations and risk of differentiated thyroid carcinoma in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition. 345 incident cases of differentiated thyroid carcinoma were individually matched to 735 controls by study centre, sex, and age, date, time, and fasting status at blood collection, follow-up duration, and for women menopausal status, use of exogenous hormones, and phase of menstrual cycle at blood collection. Serum IGF-I concentrations were measured by immunoassay, and risk of differentiated thyroid cancer in relation to IGF-I concentration was estimated using conditional logistic regression. Results: There was a positive association between IGF-I concentrations and risk of differentiated thyroid carcinoma: the odds ratio for a doubling in IGF-I concentration was 1.48 (95% confidence interval: 1.06 - 2.08; ptrend = 0.02). The positive association with IGF-I was stable over time between blood collection and cancer diagnosis. Conclusion: These findings suggest that IGF-I concentrations may be positively associated with risk of differentiated thyroid carcinoma. Impact: This study provides the first prospective evidence of a potential association between circulating IGF-I concentrations and risk of differentiated thyroid carcinoma and may prompt the further investigations needed to confirm the association.
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| 4. |
- Wang, Zhaoming, et al.
(författare)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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Ingår i: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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