Investigator

Kathryn L. Terry

Co-Scientific Director · Boston Children's Hospital, Boston Center for Endometriosis

KLTKathryn L. Terry
Papers(8)
Patterns of Associati…Prospective Analysis …Associations between …A Prospective Study C…The Association of Ki…Folate Intake and Ova…Measurement of Ovaria…Associations between …
Collaborators(10)
Shelley S. TworogerNaoko SasamotoMary K. TownsendHolly R. HarrisCassandra A. HathawayJennifer A. DohertyJose Conejo-GarciaAnna H. WuMarc T. GoodmanBritton Trabert
Institutions(7)
Brigham And Womens Ho…Moffitt Cancer CenterFred Hutch Cancer Cen…University of UtahUniversity of Souther…Cedars Sinai Medical …University of Utah

Papers

Patterns of Associations with Epidemiologic Factors by High-Grade Serous Ovarian Cancer Gene Expression Subtypes

Abstract Background: Ovarian high-grade serous carcinomas (HGSC) comprise four distinct molecular subtypes based on mRNA expression patterns, with differential survival. Understanding risk factor associations is important to elucidate the etiology of HGSC. We investigated associations between different epidemiologic risk factors and HGSC molecular subtypes. Methods: We pooled data from 11 case–control studies with epidemiologic and tumor gene expression data from custom NanoString CodeSets developed through a collaboration within the Ovarian Tumor Tissue Analysis consortium. The PrOTYPE-validated NanoString-based 55-gene classifier was used to assign HGSC gene expression subtypes. We examined associations between epidemiologic factors and HGSC subtypes in 2,070 cases and 16,633 controls using multivariable-adjusted polytomous regression models. Results: Among the 2,070 HGSC cases, 556 (27%) were classified as C1.MES, 340 (16%) as C5.PRO, 538 (26%) as C2.IMM, and 636 (31%) as C4.DIF. The key factors, including oral contraceptive use, parity, breastfeeding, and family history of ovarian cancer, were similarly associated with all subtypes. Heterogeneity was observed for several factors. Former smoking [OR = 1.25; 95% confidence interval (CI) = 1.03, 1.51] and genital powder use (OR = 1.42; 95% CI = 1.08, 1.86) were uniquely associated with C2.IMM. History of endometriosis was associated with C5.PRO (OR = 1.46; 95% CI = 0.98, 2.16) and C4.DIF (OR = 1.27; 95% CI = 0.94, 1.71) only. Family history of breast cancer (OR = 1.44; 95% CI = 1.16, 1.78) and current smoking (OR = 1.40; 95% CI = 1.11, 1.76) were associated with C4.DIF only. Conclusions: This study observed heterogeneous associations of epidemiologic and modifiable factors with HGSC molecular subtypes. Impact: The different patterns of associations may provide key information about the etiology of the four subtypes.

Prospective Analysis of Circulating Biomarkers and Ovarian Cancer Risk in the UK Biobank

Abstract Background: Risk factors have a limited ability to predict individuals at high risk of developing ovarian cancer among average-risk women, highlighting the need for discovery of novel biomarkers. In the UK Biobank, we investigated serum biomarkers commonly measured in clinical laboratory tests and ovarian cancer risk. Methods: We conducted a prospective analysis of 20 serum biomarkers and ovarian cancer risk in 232,037 female UK Biobank participants (including 1,122 incident ovarian cancer cases diagnosed from 2006 to 2020). Multivariable adjusted Cox proportional hazards models were used to examine associations between biomarkers and ovarian cancer risk overall and by histotype. FDR was used to account for multiple testing. Results: Overall, higher levels of insulin-like growth factor (IGF)-1 [RRquartile 4 vs. 1 = 0.73; 95% confidence interval (CI), 0.60–0.87; P-trend = 0.002/FDR = 0.04], HbA1c (RRquartile 4 vs. 1 = 0.74; 95% CI, 0.62–0.89; P-trend = 0.002/FDR = 0.04), and alanine aminotransferase (RRquartile 4 vs. 1 = 0.76; 95% CI, 0.63–0.91; P-trend = 0.002/FDR = 0.04) were significantly associated with lower ovarian cancer risk. When stratified by histotype, higher IGF1 levels were associated with lower risk of serous (RRquartile 4 vs. 1 = 0.73; 95% CI, 0.58–0.91; P-trend = 0.01/FDR = 0.20) and clear cell tumors (RRquartile 4 vs. 1 = 0.18; 95% CI, 0.07–0.49; P-trend = 0.001/FDR = 0.02), and higher HbA1c levels were associated with lower risk of serous tumors (RRquartile 4 vs. 1 = 0.73; 95% CI, 0.59–0.90; P-trend = 0.004/FDR = 0.08). Conclusions: We observed that higher levels of circulating IGF1, HbA1c, and alanine aminotransferase were associated with lower ovarian cancer risk. Impact: These results suggest metabolism of glucose/amino acid and insulin/IGF1 signaling pathway may be contributing to ovarian carcinogenesis. Further research is needed to replicate our findings and elucidate how systemic changes in metabolism impact ovarian carcinogenesis.

A Prospective Study Consortium for the Discovery and Validation of Early Detection Markers for Ovarian Cancer – Baseline Findings for CA125

Abstract Purpose: Epithelial ovarian cancer (EOC) is a lethal malignancy. Cancer antigen 125 (CA125), the “best” available marker for detecting EOC, has insufficient sensitivity and specificity for earlier-stage disease and is not a meaningful screening tool, motivating the search for further biomarkers. Cancer biomarker discovery is enhanced by “omics” technologies. Discovery studies for EOC biomarkers should be conducted in prediagnosis blood samples from prospective cohorts to maximize the likelihood of identifying markers that can detect disease before usual diagnosis and in earlier disease stage while reducing methodologic biases. Experimental Design: Individual cohorts with prediagnosis blood samples have insufficient sample size for such studies. Thus, we established “Prospective Early Detection Consortium for Ovarian Cancer” (“PREDICT”)—a collaboration of nine prospective studies—to assemble a sufficient number of EOC cases with blood samples collected ≤18 months before diagnosis plus controls. The 457 cases and 1,687 controls have circulating CA125 measured using a clinical assay. Results: The discrimination capacity for single CA125 measurements in samples collected <6 months prior to diagnosis was high (AUC; PREDICT overall = 0.92; range across cohorts of nonpregnant individuals = 0.89–0.98) and declined with extended time between blood collection and diagnosis. Between-cohort variability in CA125 levels and predictive performance was observed. Conclusions: Ongoing investigations in PREDICT are evaluating the early detection potential of tumor-associated autoantibodies and miRNAs using CA125 as a benchmark. PREDICT is a well-characterized resource for identifying and validating detection markers for EOC that may then be used in multimodal screening as a complement to CA125 and combined with imaging.

The Association of Kidney Function and Inflammatory Biomarkers with Epithelial Ovarian Cancer Risk

Abstract Background: One of the mechanisms of ovarian tumorigenesis is through inflammation. Kidney dysfunction is associated with increased inflammation; thus, we assessed its relationship with ovarian cancer risk. Methods: In prospectively collected samples, we evaluated the association of kidney function markers and C-reactive protein (CRP) with ovarian cancer risk in the UK Biobank. We used multivariable-adjusted Cox proportional hazards models to evaluate quartiles of serum and urine markers with ovarian cancer risk overall and by histology. We assessed effect modification by CRP (≤3.0, >3.0 mg/L). Results: Among 232,908 women (1,110 ovarian cancer cases diagnosed from 2006–2020), we observed no association between estimated glomerular filtration rate and ovarian cancer risk (Q4 vs. Q1: HR, 1.00; 95% confidence intervals, 0.83–1.22). Potassium was associated with endometrioid (Q4 vs. Q1: 0.33, 0.11–0.98) and clear cell (4.74, 1.39–16.16) tumors. Poor kidney function was associated with a nonsignificant increase in ovarian cancer risk among women with CRP>3.0 mg/L (e.g., uric acid Q4 vs. Q1; 1.23, 0.81–1.86), but not CRP≤3.0 mg/L (0.83, 0.66–1.05). Other associations did not vary across CRP categories. Conclusions: Kidney function was not clearly associated with ovarian cancer risk. Larger studies are needed to evaluate possible histology specific associations. Given the suggestive trend for increased ovarian cancer risk in women with poor kidney function and high CRP, future work is needed, particularly in populations with a high prevalence of inflammatory conditions. Impact: This study provided the first evaluation of markers of kidney function in relation to ovarian cancer risk.

Folate Intake and Ovarian Cancer Risk among Women with Endometriosis: A Case–Control Study from the Ovarian Cancer Association Consortium

Abstract Background: Although folate intake has not been associated with an increased risk of ovarian cancer overall, studies of other cancer types have suggested that high folate intake may promote carcinogenesis in precancerous lesions. Women with endometriosis (a potential precancerous lesion) have an increased risk of developing ovarian cancer; however, whether high folate intake increases risk in this group is unknown. Methods: We conducted a pooled analysis of six case–control studies from the Ovarian Cancer Association Consortium to investigate the association between folate intake and risk of ovarian cancer among women with and without self-reported endometriosis. We included 570 cases/558 controls with and 5,171/7,559 without endometriosis. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals for the association between folate intake (dietary, supplemental, and total) and ovarian cancer risk. Finally, we used Mendelian randomization (MR) to evaluate our results using genetic markers as a proxy for folate status. Results: Higher dietary folate intake was associated with an increased risk of ovarian cancer for women with endometriosis [OR, 1.37 (1.01–1.86)] but not for women without endometriosis. There was no association between supplemental folate intake and ovarian cancer risk for women with or without endometriosis. A similar pattern was seen using MR. Conclusions: High dietary folate intake may be associated with an increased risk of ovarian cancer among women with endometriosis. Impact: Women with endometriosis with high folate diets may be at increased risk of ovarian cancer. Further research is needed on the potential cancer-promoting effects of folate in this group.

Measurement of Ovarian Tumor Immune Profiles by Multiplex Immunohistochemistry: Implications for Epidemiologic Studies

Abstract Background: Despite the immunogenic nature of many ovarian tumors, treatment with immune checkpoint therapies has not led to substantial improvements in ovarian cancer survival. To advance population-level research on the ovarian tumor immune microenvironment, it is critical to understand methodologic issues related to measurement of immune cells on tissue microarrays (TMA) using multiplex immunofluorescence (mIF) assays. Methods: In two prospective cohorts, we collected formalin-fixed, paraffin-embedded ovarian tumors from 486 cases and created seven TMAs. We measured T cells, including several sub-populations, and immune checkpoint markers on the TMAs using two mIF panels. We used Spearman correlations, Fisher exact tests, and multivariable-adjusted beta-binomial models to evaluate factors related to immune cell measurements in TMA tumor cores. Results: Between-core correlations of intratumoral immune markers ranged from 0.52 to 0.72, with more common markers (e.g., CD3+, CD3+CD8+) having higher correlations. Correlations of immune cell markers between the whole core, tumor area, and stromal area were high (range 0.69–0.97). In multivariable-adjusted models, odds of T-cell positivity were lower in clear cell and mucinous versus type II tumors (ORs, 0.13–0.48) and, for several sub-populations, were lower in older tissue (sample age > 30 versus ≤ 10 years; OR, 0.11–0.32). Conclusions: Overall, high correlations between cores for immune markers measured via mIF support the use of TMAs in studying ovarian tumor immune infiltration, although very old samples may have reduced antigenicity. Impact: Future epidemiologic studies should evaluate differences in the tumor immune response by histotype and identify modifiable factors that may alter the tumor immune microenvironment.

Associations between Parity, History of Breastfeeding, and T-cell Profile of Ovarian Tumors

Abstract Background: Parity and breastfeeding are associated with systemic changes in maternal inflammation and reduced risk of ovarian cancer, but little is known about their impact on the ovarian tumor immune microenvironment. Methods: We evaluated the associations of self-reported parity and history of breastfeeding with tumor-infiltrating T cells among 1,706 ovarian carcinoma cases with tumor tissue collected across four studies. The abundance of tumor-infiltrating T cells was measured by multiplex immunofluorescence in tumor tissue microarrays. ORs and 95% confidence intervals (CI) for the positivity of tumor immune cells were calculated using beta-binomial models and stratified by histotype. Results: Compared with ovarian tumors in nulliparous women, there was no association between parity and ovarian tumor T-cell abundance among all histotypes combined but suggestion of increased cytotoxic T cells and T-cell exhaustion among parous women with clear-cell tumors. When restricted to parous women, history of breastfeeding was associated with increased odds for all T-cell types [i.e., total T, cytotoxic T, helper T (Th), regulatory T, and exhausted T cells], with ORs ranging from 1.11 to 1.42. For every 6 months of breastfeeding, we observed increased odds of activated Th-cell infiltration (CD3+CD4+CD69+; OR, 1.13, 95% CI, 0.99–1.29), with a similar association for high-grade serous tumors, but lower odds in clear-cell tumors (OR, 0.43, 95% CI, 0.21–0.87). Conclusions: History of breastfeeding may alter the ovarian tumor immune microenvironment by modulating the abundance of tumor-infiltrating T cells. Impact: Although replication is required, history of breastfeeding may play a role in the activation of the ovarian tumor immune response.

355Works
8Papers
65Collaborators
Ovarian NeoplasmsBiomarkers, TumorTumor MicroenvironmentEarly Detection of CancerCystadenocarcinoma, SerousNeoplasm GradingLymphocytes, Tumor-Infiltrating

Positions

2016–

Co-Scientific Director

Boston Children's Hospital · Boston Center for Endometriosis

2015–

Associate Professor

Harvard T.H. Chan School of Public Health · Epidemiology

2015–

Associate Professor

Harvard Medical School · Harvard Medical School

2006–

Associate Epidemiologist

The Brigham and Women's Hospital, Inc. · Obstetrics, Gynecology and Reproductive Biology

2007–

Assistant Professor

Harvard School of Public Health · Epidemiology

2007–

Assistant Professor

Harvard Medical School · Obstetrics, Gynecology, and Reproductive Biology

2006–

Instructor

Harvard School of Public Health · Epidemiology

2006–

Instructor

Harvard Medical School · Obstetrics, Gynecology, and Reproductive Biology

Education

2006

Postdoctoral Fellow

Harvard School of Public Health · Genetic Epidemiology

2005

ScD

Harvard School of Public Health · Epidemiology

1995

BA

Haverford College · History

Country

US