| 31. |
- Lin, HY, et al.
(författare)
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KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness
- 2021
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 9264-
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Tidskriftsartikel (refereegranskat)abstract
- Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10–9) and 3145 (P < 1 × 10–5) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.
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| 33. |
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| 34. |
- Mao, W, et al.
(författare)
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Bupi Yishen Formula Versus Losartan for Non-Diabetic Stage 4 Chronic Kidney Disease: A Randomized Controlled Trial
- 2021
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Ingår i: Frontiers in pharmacology. - : Frontiers Media SA. - 1663-9812. ; 11, s. 627185-
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Tidskriftsartikel (refereegranskat)abstract
- Chinese herbal medicine (CHM) might have benefits in patients with non-diabetic chronic kidney disease (CKD), but there is a lack of high-quality evidence, especially in CKD4. This study aimed to assess the efficacy and safety of Bupi Yishen Formula (BYF) vs. losartan in patients with non-diabetic CKD4. This trial was a multicenter, double-blind, double-dummy, randomized controlled trial that was carried out from 11-08-2011 to 07-20-2015. Patients were assigned (1:1) to receive either BYF or losartan for 48 weeks. The primary outcome was the change in the slope of the estimated glomerular filtration rate (eGFR) over 48 weeks. The secondary outcomes were the composite of end-stage kidney disease, death, doubling of serum creatinine, stroke, and cardiovascular events. A total of 567 patients were randomized to BYF (n = 283) or losartan (n = 284); of these, 549 (97%) patients were included in the final analysis. The BYF group had a slower renal function decline particularly prior to 12 weeks over the 48-week duration (between-group mean difference of eGFR slopes: −2.25 ml/min/1.73 m2/year, 95% confidence interval [CI]: −4.03,−0.47), and a lower risk of composite outcome of death from any cause, doubling of serum creatinine level, end-stage kidney disease (ESKD), stroke, or cardiovascular events (adjusted hazard ratio = 0.61, 95%CI: 0.44,0.85). No significant between-group differences were observed in the incidence of adverse events. We conclude that BYF might have renoprotective effects among non-diabetic patients with CKD4 in the first 12 weeks and over 48 weeks, but longer follow-up is required to evaluate the long-term effects.Clinical Trial Registration:http://www.chictr.org.cn, identifier ChiCTR-TRC-10001518.
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| 35. |
- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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