| 1. |
- Jiang, X., et al.
(författare)
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Shared heritability and functional enrichment across six solid cancers
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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| 2. |
- Barausse, Enrico, et al.
(författare)
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Prospects for fundamental physics with LISA
- 2020
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Ingår i: General Relativity and Gravitation. - : SPRINGER/PLENUM PUBLISHERS. - 0001-7701 .- 1572-9532. ; 52:8
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA,we present here a sample of what we view as particularly promising fundamental physics directions. We organize these directions through a "science-first" approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. The classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics.
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| 3. |
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| 4. |
- Jaffee, E. M., et al.
(författare)
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Future cancer research priorities in the USA: a Lancet Oncology Commission
- 2017
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Ingår i: Lancet Oncology. - 1470-2045. ; 18:11
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Forskningsöversikt (refereegranskat)abstract
- We are in the midst of a technological revolution that is providing new insights into human biology and cancer. In this era of big data, we are amassing large amounts of information that is transforming how we approach cancer treatment and prevention. Enactment of the Cancer Moonshot within the 21st Century Cures Act in the USA arrived at a propitious moment in the advancement of knowledge, providing nearly US$ 2 billion of funding for cancer research and precision medicine. In 2016, the Blue Ribbon Panel (BRP) set out a roadmap of recommendations designed to exploit new advances in cancer diagnosis, prevention, and treatment. Those recommendations provided a high-level view of how to accelerate the conversion of new scientific discoveries into effective treatments and prevention for cancer. The US National Cancer Institute is already implementing some of those recommendations. As experts in the priority areas identified by the BRP, we bolster those recommendations to implement this important scientific roadmap. In this Commission, we examine the BRP recommendations in greater detail and expand the discussion to include additional priority areas, including surgical oncology, radiation oncology, imaging, health systems and health disparities, regulation and financing, population science, and oncopolicy. We prioritise areas of research in the USA that we believe would accelerate efforts to benefit patients with cancer. Finally, we hope the recommendations in this report will facilitate new international collaborations to further enhance global efforts in cancer control.
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| 7. |
- Dareng, EO, et al.
(författare)
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Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
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Ingår i: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
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Tidskriftsartikel (refereegranskat)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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| 9. |
- Antoniou, A. C., et al.
(författare)
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Common breast cancer susceptibility alleles and the risk of breast cancer for BRCA1 and BRCA2 mutation carriers : Implications for risk prediction
- 2010
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Ingår i: Cancer Research. - : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 70:23, s. 9742-9754
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Tidskriftsartikel (refereegranskat)abstract
- The known breast cancer susceptibility polymorphisms in FGFR2, TNRC9/TOX3, MAP3K1, LSP1, and 2q35 confer increased risks of breast cancer for BRCA1 or BRCA2 mutation carriers. We evaluated the associations of 3 additional single nucleotide polymorphisms (SNPs), rs4973768 in SLC4A7/NEK10, rs6504950 in STXBP4/COX11, and rs10941679 at 5p12, and reanalyzed the previous associations using additional carriers in a sample of 12,525 BRCA1 and 7,409 BRCA2 carriers. Additionally, we investigated potential interactions between SNPs and assessed the implications for risk prediction. The minor alleles of rs4973768 and rs10941679 were associated with increased breast cancer risk for BRCA2 carriers (per-allele HR = 1.10, 95% CI: 1.03-1.18, P = 0.006 and HR = 1.09, 95% CI: 1.01-1.19, P = 0.03, respectively). Neither SNP was associated with breast cancer risk for BRCA1 carriers, and rs6504950 was not associated with breast cancer for either BRCA1 or BRCA2 carriers. Of the 9 polymorphisms investigated, 7 were associated with breast cancer for BRCA2 carriers (FGFR2, TOX3, MAP3K1, LSP1, 2q35, SLC4A7, 5p12, P = 7 × 10-11 - 0.03), but only TOX3 and 2q35 were associated with the risk for BRCA1 carriers (P = 0.0049, 0.03, respectively). All risk-associated polymorphisms appear to interact multiplicatively on breast cancer risk for mutation carriers. Based on the joint genotype distribution of the 7 risk-associated SNPs in BRCA2 mutation carriers, the 5% of BRCA2 carriers at highest risk (i.e., between 95th and 100th percentiles) were predicted to have a probability between 80% and 96% of developing breast cancer by age 80, compared with 42% to 50% for the 5% of carriers at lowest risk. Our findings indicated that these risk differences might be sufficient to influence the clinical management of mutation carriers.
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