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- Conti, David, V, et al.
(författare)
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Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
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Tidskriftsartikel (refereegranskat)abstract
- Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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| 2. |
- Campi, Riccardo, et al.
(författare)
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Novel Liquid Biomarkers and Innovative Imaging for Kidney Cancer Diagnosis : What Can Be Implemented in Our Practice Today? A Systematic Review of the Literature
- 2021
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Ingår i: European Urology Oncology. - : Elsevier. - 2588-9311. ; 4:1, s. 22-41
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Forskningsöversikt (refereegranskat)abstract
- CONTEXT: The epidemiological signature of renal cell carcinoma (RCC) during the past decades is explained by overdetection and overtreatment of indolent cancers; furthermore, a non-negligible proportion of patients undergoing surgery for suspected RCC harbour benign renal tumours. As the gold standard for RCC diagnosis remains histopathological analysis of surgical or biopsy specimens, implementation of noninvasive diagnostic strategies to discriminate between benign and malignant renal masses is an urgent unmet need. OBJECTIVE: To systematically review novel liquid biomarkers and imaging modalities for RCC diagnosis. EVIDENCE ACQUISITION: A systematic review of the recent English-language literature was conducted according to the European Association of Urology guidelines and the PRISMA statement recommendations (PROSPERO ID: CRD42020190773) using the MEDLINE, Cochrane Central Register of Controlled Trials, Web of Science, and ClinicalTrials.gov databases. Risk-of-bias assessment was performed according to the QUADAS 2 tool. EVIDENCE SYNTHESIS: Overall, 15 studies (six on biomarkers and nine on imaging) and eight clinical trials were included. None of the biomarkers or imaging modalities has been validated or shown to have a distinct clinical value for RCC. Specific combinations of urinary cell-free and exosomal miRNAs, urinary miR-15a, and specific panels of urinary metabolites assessed by metabolomics appear promising. In addition, machine/deep learning algorithms and radiomics applied to cross-sectional images may have potential to improve RCC diagnosis. Most studies are limited by the retrospective design, size, and lack of external validation. CONCLUSIONS: Liquid biomarkers or imaging modalities are not ready for integration in the clinic and further well-designed studies must validate preliminary findings and explore utility in clinical decision-making. PATIENT SUMMARY: We provide a comprehensive overview of the currently available biomarkers (measured in blood or urine) and novel imaging tests (other than conventional imaging) to discriminate kidney cancer from benign renal masses in a noninvasive fashion. None of the biomarkers or imaging modalities studied was validated or added clinical value; therefore, none of them can be implemented in the clinic. However, these approaches appear to be promising for improving the diagnosis of kidney cancer in the future.
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