The journal of applied laboratory medicine · 2026
Correlates of Serum Concentrations of Biomarkers Relevant to Ovarian Cancer Screening.
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Akonde Maxwell, Graybill Whitney Spannuth, Clay-Gilmour Alyssa, Zhang Jiajia, Alberg Anthony J
Аннотация
BACKGROUND: Many biomarkers have been evaluated as potential early detection markers for ovarian cancer. Better understanding of factors associated with inter-individual variation in circulating concentrations of these biomarkers is useful for optimizing their clinical utility for early detection. The study objective was to characterize the associations of sociodemographic-, lifestyle-, and health-related factors in relation to circulating ovarian biomarker concentrations in cancer-free women.
METHODS: The associations between the independent variables and concentrations of 20 biomarkers were examined in a cross-sectional study of 913 women without ovarian cancer who participated in the ovarian cancer screening arm of the Prostate Lung Colorectal and Ovarian (PLCO) Cancer Screening Trial.
RESULTS: Older age was significantly associated with trends in concentrations of ten biomarkers, eight that increased with age (human epididymis protein 4 [HE4], beta-2-microglobulin [B2M], epidermal growth factor receptor [EGFR], insulin-like growth factor binding protein 2 [IGFBPII], kallikrein-related peptidase [KLK6], mesothelin [MSLN], matrix metalloproteinase-3 [MMP3], and spondin 2 [SPON2]) and two that decreased with age (insulin-like growth factor 2 [IGFII] and inter-alpha-trypsin inhibitor heavy chain H4 [ITIH4]). Compared to women with no family history of breast or ovarian cancer, those with a positive family history had significantly higher concentrations of B2M, EGFR, and hepcidin and lower concentrations of cancer antigen 125 (CA125) and cancer antigen 72.4 (CA72.4). Post hoc case-control comparisons showed case-control heterogeneity concentrated in specific biomarkers; for example, case-control differences for cancer antigen 15.3 (CA15.3) were statistically significant for all 11 independent variables.
CONCLUSION: Significant trends were observed between age and circulating concentrations of 10 of the 20 biomarkers studied. The strong, consistent findings with age support the need to consider age when assigning thresholds for biomarkers being evaluated for the early detection of ovarian cancer. Integrating data from cancer cases provides valuable context for assessing the generalizability of findings.
METHODS: The associations between the independent variables and concentrations of 20 biomarkers were examined in a cross-sectional study of 913 women without ovarian cancer who participated in the ovarian cancer screening arm of the Prostate Lung Colorectal and Ovarian (PLCO) Cancer Screening Trial.
RESULTS: Older age was significantly associated with trends in concentrations of ten biomarkers, eight that increased with age (human epididymis protein 4 [HE4], beta-2-microglobulin [B2M], epidermal growth factor receptor [EGFR], insulin-like growth factor binding protein 2 [IGFBPII], kallikrein-related peptidase [KLK6], mesothelin [MSLN], matrix metalloproteinase-3 [MMP3], and spondin 2 [SPON2]) and two that decreased with age (insulin-like growth factor 2 [IGFII] and inter-alpha-trypsin inhibitor heavy chain H4 [ITIH4]). Compared to women with no family history of breast or ovarian cancer, those with a positive family history had significantly higher concentrations of B2M, EGFR, and hepcidin and lower concentrations of cancer antigen 125 (CA125) and cancer antigen 72.4 (CA72.4). Post hoc case-control comparisons showed case-control heterogeneity concentrated in specific biomarkers; for example, case-control differences for cancer antigen 15.3 (CA15.3) were statistically significant for all 11 independent variables.
CONCLUSION: Significant trends were observed between age and circulating concentrations of 10 of the 20 biomarkers studied. The strong, consistent findings with age support the need to consider age when assigning thresholds for biomarkers being evaluated for the early detection of ovarian cancer. Integrating data from cancer cases provides valuable context for assessing the generalizability of findings.