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- Enroth, Stefan, 1976-, et al.
(author)
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A two-step strategy for identification of plasma protein biomarkers for endometrial and ovarian cancer
- 2018
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In: Clinical Proteomics. - : Springer Science and Business Media LLC. - 1542-6416 .- 1559-0275. ; 15
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Journal article (peer-reviewed)abstract
- BackgroundOver 500,000 women worldwide are diagnosed with ovarian or endometrial cancer each year. We have used a two-step strategy to identify plasma proteins that could be used to improve the diagnosis of women with an indication of gynecologic tumor and in population screening.MethodsIn the discovery step we screened 441 proteins in plasma using the proximity extension assay (PEA) and five Olink Multiplex assays (CVD II, CVD III, INF I, ONC II, NEU I) in women with ovarian cancer (n=106), endometrial cancer (n=74), benign ovarian tumors (n=150) and healthy population controls (n=399). Based on the discovery analyses a set of 27 proteins were selected and two focused multiplex PEA assays were developed. In a replication step the focused assays were used to study an independent set of cases with ovarian cancer (n=280), endometrial cancer (n=228), women with benign ovarian tumors (n=76) and healthy controls (n=57).ResultsIn the discovery step, 27 proteins that showed an association to cancer status were identified. In the replication analyses, the focused assays distinguished benign tumors from ovarian cancer stage III-IV with a sensitivity of 0.88 and specificity of 0.92 (AUC=0.92). The assays had a significantly higher AUC for distinguishing benign tumors from late stage ovarian cancer than using CA125 and HE4 (p=9.56e-22). Also, population controls could be distinguished from ovarian cancer stage III-IV with a sensitivity of 0.85 and a specificity of 0.92 (AUC=0.89).ConclusionThe PEA assays represent useful tools for identification of new biomarkers for gynecologic cancers. The selected protein assays could be used to distinguish benign tumors from ovarian and endometrial cancer in women diagnosed with an unknown suspicious pelvic mass. The panels could also be used in population screening, for identification of women in need of specialized gynecologic transvaginal ultrasound examination.FundingThe Swedish Cancer Foundation, Vinnova (SWELIFE), The Foundation for Strategic Research (SSF), Assar Gabrielsson Foundation.
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- Enroth, Stefan, 1976-, et al.
(author)
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High throughput proteomics identifies a high-accuracy 11 plasma protein biomarker signature for ovarian cancer
- 2019
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 2
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Journal article (peer-reviewed)abstract
- Ovarian cancer is usually detected at a late stage and the overall 5-year survival is only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 593 proteins in three cohorts of patients with ovarian cancer and benign tumors, using the proximity extension assay (PEA). A combinatorial strategy was developed for identification of different multivariate biomarker signatures. A final model consisting of 11 biomarkers plus age was developed into a multiplex PEA test reporting in absolute concentrations. The final model was evaluated in a fourth independent cohort and has an AUC = 0.94, PPV = 0.92, sensitivity = 0.85 and specificity = 0.93 for detection of ovarian cancer stages I-IV. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.
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- Rukh, Gull, et al.
(author)
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Dietary starch intake modifies the relation between copy number variation in the salivary amylase gene and BMI
- 2017
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In: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165. ; 106:1, s. 256-262
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Journal article (peer-reviewed)abstract
- Background: Studies have shown conflicting associations between the salivary amylase gene (AMY1) copy number and obesity. Salivary amylase initiates starch digestion in the oral cavity; starch is a major source of energy in the diet. Objective: We investigated the association between AMY1 copy number and obesity traits, and the effect of the interaction between AMY1 copy number and starch intake on these obesity traits. Design: We first assessed the association between AMY1 copy number (genotyped by digital droplet polymerase chain reaction) and obesity traits in 4800 individuals without diabetes (mean age: 57 y; 60% female) from the Malmo "Diet and Cancer Cohort. Then we analyzed interactions between AMY1 copy number and energyadjusted starch intake (obtained by a modified diet history method) on body mass index (BMI) and body fat percentage. Results: AMY1 copy number was not associated with BMI (P = 0.80) or body fat percentage (P = 0.38). We observed a significant effect of the interaction between AMY1 copy number and starch intake on BMI (P-interaction = 0.007) and body fat percentage (P-interaction = 0.03). Upon stratification by dietary starch intake, BMI tended to decrease with increasing AMY1 copy numbers in the low-starch intake group (P = 0.07) and tended to increase with increasing AMY1 copy numbers in the high-starch intake group (P = 0.08). The lowest mean BMI was observed in the group of participants with a low AMY1 copy number and a high dietary intake of starch. Conclusions: Our findings suggest an effect of the interaction between starch intake and AMY1 copy number on obesity. Individuals with high starch intake but low genetic capacity to digest starch had the lowest BMI, potentially because larger amounts of undigested starch are transported through the gastrointestinal tract, contributing to fewer calories extracted from ingested starch.
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