ORCID Profile
0000-0001-8420-9167
Current Organisation
Brigham and Women's Hospital
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Publisher: American Association for Cancer Research (AACR)
Date: 2020
DOI: 10.1158/1055-9965.EPI-19-0734
Abstract: Laterality of epithelial ovarian tumors may reflect the underlying carcinogenic pathways and origins of tumor cells. We pooled data from 9 prospective studies participating in the Ovarian Cancer Cohort Consortium. Information on measures of tumor size or tumor dominance was extracted from surgical pathology reports or obtained through cancer registries. We defined dominant tumors as those restricted to one ovary or where the dimension of one ovary was at least twice as large as the other, and nondominant tumors as those with similar dimensions across the two ovaries or peritoneal tumors. Competing risks Cox models were used to examine whether associations with reproductive and hormonal risk factors differed by ovarian tumor dominance. Of 1,058 ovarian cancer cases with tumor dominance information, 401 were left-dominant, 363 were right-dominant, and 294 were nondominant. Parity was more strongly inversely associated with risk of dominant than nondominant ovarian cancer (Pheterogeneity = 0.004). Ever use of oral contraceptives (OC) was associated with lower risk of dominant tumors, but was not associated with nondominant tumors (Pheterogeneity = 0.01). Higher body mass index was associated with higher risk of left-dominant tumors, but not significantly associated with risk of right-dominant or nondominant tumors (Pheterogeneity = 0.08). These data suggest that reproductive and hormonal risk factors appear to have a stronger impact on dominant tumors, which may have an ovarian or endometriosis origin. Examining the associations of ovarian cancer risk factors by tumor dominance may help elucidate the mechanisms through which these factors influence ovarian cancer risk.
Publisher: Elsevier BV
Date: 06-2016
Publisher: American Diabetes Association
Date: 08-11-2018
DOI: 10.2337/DB18-0892
Abstract: Numerous studies have investigated in idual biomarkers in relation to risk of type 2 diabetes. However, few have considered the interconnectivity of these biomarkers in the etiology of diabetes as well as the potential changes in the biomarker correlation network during diabetes development. We conducted a secondary analysis of 27 plasma biomarkers representing glucose metabolism, inflammation, adipokines, endothelial dysfunction, IGF axis, and iron store plus age and BMI at blood collection from an existing case-control study nested in the Nurses’ Health Study (NHS), including 1,303 incident diabetes case subjects and 1,627 healthy women. A correlation network was constructed based on pairwise Spearman correlations of the above factors that were statistically different between case and noncase subjects using permutation tests (P & 0.0005). We further evaluated the network structure separately among diabetes case subjects diagnosed & , 5–10, and & years after blood collection versus noncase subjects. Although pairwise biomarker correlations tended to have similar directions comparing diabetes case subjects to noncase subjects, most correlations were stronger in noncase than in case subjects, with the largest differences observed for the insulin/HbA1c and leptin/adiponectin correlations. Leptin and soluble leptin receptor were two hubs of the network, with large numbers of different correlations with other biomarkers in case versus noncase subjects. When examining the correlation network by timing of diabetes onset, there were more perturbations in the network for case subjects diagnosed & years versus & years after blood collection, with consistent differential correlations of insulin and HbA1c. C-peptide was the most highly connected node in the early-stage network, whereas leptin was the hub for mid- or late-stage networks. Our results suggest that perturbations of the diabetes-related biomarker network may occur decades prior to clinical recognition. In addition to the persistent dysregulation between insulin and HbA1c, our results highlight the central role of the leptin system in diabetes development.
Location: United States of America
No related grants have been discovered for Tianyi Huang.