Investigator

Cassandra A. Hathaway

Moffitt Cancer Center, Cancer Epidemiology

CAHCassandra A. Hath…
Papers(10)
Prospective Analysis …Lifetime Exposure to …Inequities in the Imp…The relationship of l…The Association of Ki…Germline Mutations in…Measurement of Ovaria…Ovarian Cancer Risk i…Prolactin and Risk of…The association of re…
Collaborators(10)
Shelley S. TworogerMary K. TownsendKathryn L. TerryBritton TrabertJonathan V. NguyenJose Conejo-GarciaBrooke L. FridleyTianyi WangCarlos Moran SeguraDaryoush Saeed-Vafa
Institutions(3)
Moffitt Cancer CenterBoston Children's Hos…University of Utah

Papers

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.

Lifetime Exposure to Cigarette Smoke, B-Cell Tumor Immune Infiltration, and Immunoglobulin Abundance in Ovarian Tumors

Abstract Background: Cigarette smoke exposure has been linked to systemic immune dysfunction, including for B-cell and immunoglobulin (Ig) production, and poor outcomes in patients with ovarian cancer. No study has evaluated the impact of smoke exposure across the life-course on B-cell infiltration and Ig abundance in ovarian tumors. Methods: We measured markers of B and plasma cells and Ig isotypes using multiplex immunofluorescence on 395 ovarian cancer tumors in the Nurses’ Health Study (NHS)/NHSII. We conducted beta-binomial analyses evaluating odds ratios (OR) and 95% confidence intervals (CI) for positivity of immune markers by cigarette exposure among cases and Cox proportional hazards models to evaluate hazard ratios (HR) and 95% CI for developing tumors with low (<median) or high (≥median) immune cell/Ig percentage. Results: There were no associations between smoke exposure and B-cell or IgM infiltration in ovarian tumors. Among cases, we observed higher odds of IgA+ among ever smokers (OR, 1.54; 95% CI, 1.14–2.07) and ever smokers with no parental smoke exposure (OR, 2.03; 95% CI, 1.18–3.49) versus never smokers. Women with parental cigarette smoke exposure versus not had higher risk of developing ovarian cancer with low IgG+ (HR, 1.51; 95% CI, 1.10–2.09), whereas ever versus never smokers had a lower risk (HR, 0.74; 95% CI, 0.56–0.99). Conclusions: Ever smoking was associated with increased odds of IgA in ovarian tumors. Impact: IgA has been associated with improved ovarian cancer outcomes, suggesting that although smoking is associated with poor outcomes in patients with ovarian cancer, it may lead to improved tumor immunogenicity.

The relationship of lifetime history of depression on the ovarian tumor immune microenvironment

Depression is associated with a higher ovarian cancer risk. Prior work suggests that depression can lead to systemic immune suppression, which could potentially alter the anti-tumor immune response. We evaluated the association of pre-diagnosis depression with features of the anti-tumor immune response, including T and B cells and immunoglobulins, among women with ovarian tumor tissue collected in three studies, the Nurses' Health Study (NHS; n = 237), NHSII (n = 137) and New England Case-Control Study (NECC; n = 215). Women reporting depressive symptoms above a clinically relevant cut-point, antidepressant use, or physician diagnosis of depression at any time prior to diagnosis of ovarian cancer were considered to have pre-diagnosis depression. Multiplex immunofluorescence was performed on tumor tissue microarrays to measure immune cell infiltration. In pooled analyses, we estimated odds ratios (OR) and 95% confidence intervals (CI) for the positivity of tumor immune cells using a beta-binomial model comparing those with and without depression. We used Bonferroni corrections to adjust for multiple comparisons. We observed no statistically significant association between depression status and any immune markers at the Bonferroni corrected p-value of 0.0045; however, several immune markers were significant at a nominal p-value of 0.05. Specifically, there were increased odds of having recently activated cytotoxic (CD3 Our results provide suggestive evidence that depression may influence ovarian cancer outcomes through changes in the tumor immune microenvironment, including increasing T cell activation and exhaustion and reducing antibody-producing B cells. Further studies with clinical measures of depression and larger samples are needed to confirm these results.

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.

Germline Mutations in 12 Genes and Risk of Ovarian Cancer in Three Population-Based Cohorts

Abstract Background: With the widespread use of multigene panel genetic testing, population-based studies are necessary to accurately assess penetrance in unselected individuals. We evaluated the prevalence of germline pathogenic or likely pathogenic variants (mutations) in 12 cancer-predisposition genes and associations with ovarian cancer risk in three population-based prospective studies [Nurses’ Health Study (NHS), NHSII, Cancer Prevention Study II]. Methods: We included women with epithelial ovarian or peritoneal cancer (n = 776) and controls who were alive and had at least one intact ovary at the time of the matched case diagnosis (n = 1,509). Germline DNA was sequenced for mutations in 12 genes. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for ovarian cancer risk by mutation status. Results: The mutation frequency across all 12 genes was 11.2% in cases and 3.3% in controls (P < 0.0001). BRCA1 and BRCA2 were the most frequently mutated (3.5% and 3.8% of cases and 0.3% and 0.5% of controls, respectively) and were associated with increased ovarian cancer risk [OR, BRCA1 = 12.38; 95% confidence interval (CI) = 4.72–32.45; OR, BRCA2 = 9.18; 95% CI = 3.98–21.15]. Mutation frequencies for the other genes were ≤1.0% and only PALB2 was significantly associated with risk (OR = 5.79; 95% CI = 1.09–30.83). There was no difference in survival for women with a BRCA germline mutation versus no mutation. Conclusions: Further research is needed to better understand the role of other mutations in ovarian cancer among unselected populations. Impact: Our data support guidelines for germline genetic testing for BRCA1 and BRCA2 among women diagnosed with epithelial ovarian cancer; testing for PALB2 may be warranted.

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.

Ovarian Cancer Risk in Relation to Blood Cholesterol and Triglycerides

Abstract Background: The association between circulating cholesterol and triglyceride levels and ovarian cancer risk remains unclear. Methods: We prospectively evaluated the association between cholesterol [total, low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C)] and triglycerides and ovarian cancer incidence in a case–control study nested in the Nurses' Health Study (NHS) and NHSII cohorts and a longitudinal analysis in the UK Biobank. Results: A total of 290 epithelial ovarian cancer cases in the NHS/NHSII and 551 cases in UK Biobank were diagnosed after blood collection. We observed a reduced ovarian cancer risk comparing the top to bottom quartile of total cholesterol [meta-analysis relative risk (95% confidence interval): 0.81 (0.65–1.01), Ptrend 0.06], with no heterogeneity across studies (Pheterogeneity = 0.74). Overall, no clear patterns were observed for HDL-C, LDL-C, or triglycerides and ovarian cancer risk. Comparing triglyceride levels at clinically relevant cut-off points (>200 vs. ≤200 mg/dL) for cases diagnosed more than 2 years after blood draw saw a positive relationship with risk [1.57 (1.03–2.42); Pheterogeneity = 0.003]. Results were similar by serous/non-serous histotype, menopausal status/hormone use, and body mass index. Conclusions: Data from two large cohorts in the United States and United Kingdom suggest that total cholesterol levels may be inversely associated with ovarian cancer risk, while triglycerides may be positively associated with risk when assessed at least 2 years before diagnosis, albeit both associations were modest. Impact: This analysis of two large prospective studies suggests that circulating lipid levels are not strongly associated with ovarian cancer risk. The positive triglyceride–ovarian cancer association warrants further evaluation.

Prolactin and Risk of Epithelial Ovarian Cancer

Abstract Background: Prolactin is synthesized in the ovaries and may play a role in ovarian cancer etiology. One prior prospective study observed a suggestive positive association between prolactin levels and risk of ovarian cancer. Methods: We conducted a pooled case–control study of 703 cases and 864 matched controls nested within five prospective cohorts. We used unconditional logistic regression to calculate adjusted odds ratios (OR) and 95% confidence intervals (CI) for the association between prolactin and ovarian cancer risk. We examined heterogeneity by menopausal status at blood collection, body mass index (BMI), age, and histotype. Results: Among women with known menopausal status, we observed a positive trend in the association between prolactin and ovarian cancer risk (Ptrend = 0.045; OR, quartile 4 vs. 1 = 1.34; 95% CI = 0.97–1.85), but no significant association was observed for premenopausal or postmenopausal women individually (corresponding OR = 1.38; 95% CI = 0.74–2.58; Ptrend = 0.32 and OR = 1.41; 95% CI = 0.93–2.13; Ptrend = 0.08, respectively; Pheterogeneity = 0.91). In stratified analyses, we observed a positive association between prolactin and risk for women with BMI ≥ 25 kg/m2, but not BMI < 25 kg/m2 (corresponding OR = 2.68; 95% CI = 1.56–4.59; Ptrend < 0.01 and OR = 0.90; 95% CI = 0.58–1.40; Ptrend = 0.98, respectively; Pheterogeneity < 0.01). Associations did not vary by age, postmenopausal hormone therapy use, histotype, or time between blood draw and diagnosis. Conclusions: We found a trend between higher prolactin levels and increased ovarian cancer risk, especially among women with a BMI ≥ 25 kg/m2. Impact: This work supports a previous study linking higher prolactin with ovarian carcinogenesis in a high adiposity setting. Future work is needed to understand the mechanism underlying this association.

The association of resistance training with risk of ovarian cancer

ABSTRACTBackgroundIncreasing evidence, including multiple putative inflammatory risk factors (e.g., c‐reactive protein, and adiposity), supports that inflammation plays an important role in ovarian carcinogenesis. Resistance training (RT) is associated with lower levels of circulating inflammatory markers, independent of physical activity.MethodsWe evaluated the relationship between RT and risk of ovarian cancer accounting for other physical activity (e.g., walking) in two large prospective cohorts, the Nurses’ Health Study (NHS) and NHSII.Key ResultsIn total, analyses included 42,005 NHS participants (2000–2016) and 67,289 NHSII participants (2001–2017) with RT assessed every 4 years. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of RT with ovarian cancer risk overall and by tumor subtype, adjusting for known and putative ovarian cancer risk factors. We identified a total of 609 cases over 1,748,884 person‐years. No association was observed with overall ovarian cancer risk (RT ≥60 vs 0 min/wk, HR = 0.95, 95%CI: 0.74–1.22) or by histotype (comparable HR = 0.86 and 0.98 for type I and II tumors, respectively). Results did not differ by body mass index (Pinteraction = 0.97), or other physical activity (Pinteraction = 0.31).Conclusions & InferencesWe observed no evidence that moderate levels of RT were associated with risk of ovarian cancer. Further investigations are required to confirm these findings.

226Works
10Papers
38Collaborators
Ovarian NeoplasmsBiomarkers, TumorNeoplasmsCarcinoma, Ovarian EpithelialCancer SurvivorsTumor MicroenvironmentSkin NeoplasmsLymphocytes, Tumor-Infiltrating

Positions

Researcher

Moffitt Cancer Center · Cancer Epidemiology

2023–

Senior Epidemiologist

Westat (United States) · Clinical Research Practice

Education

2023

PhD

Nova Southeastern University · Health Science

2017

Graduate Certificate

University of South Florida · Public Health

2016

Masters

University of South Florida · Public Health

2015

Bachelors

University of South Florida · Public Health

Country

US