Diagnostic and prognostic potential of the microbiome in ovarian cancer treatment response.

Ovarian cancer (OC) is the second most common gynecological malignancy and the fifth leading cause of death due to cancer in women in the United States mainly due to the late-stage diagnosis of this cancer. It is, therefore, critical to identify potential indicators to aid in early detection and diagnosis of this disease. We investigated the microbiome associated with OC and its potential role in detection, progression as well as prognosis of the disease. We identified a distinct OC microbiome with general enrichment of several microbial taxa, including Dialister, Corynebacterium, Prevotella, and Peptoniphilus in the OC cohort in all body sites excluding stool and omentum which were not sampled from the benign cohort. These taxa were, however, depleted in the advanced-stage and high-grade OC patients compared to early-stage and low-grade OC patients suggestive of decrease accumulation in advanced disease and could serve as potential indicators for early detection of OC. Similarly, we also observed the accumulation of these mainly pathogenic taxa in OC patients with adverse treatment outcomes compared to those without events and could also serve as potential indicators for predicting patients' responses to treatment. These findings provide important insights into the potential use of the microbiome as indicators in (1) early detection of and screening for OC and (2) predicting patients' response to treatment. Given the limited number of patients enrolled in the study, these results would need to be further investigated and confirmed in a larger study.

CHFR and Paclitaxel Sensitivity of Ovarian Cancer.

The poly(ADP-ribose) binding protein CHFR regulates cellular responses to mitotic stress. The deubiquitinase UBC13, which regulates CHFR levels, has been associated with better overall survival in paclitaxel-treated ovarian cancer. Despite the extensive use of taxanes in the treatment of ovarian cancer, little is known about expression of CHFR itself in this disease. In the present study, tissue microarrays containing ovarian carcinoma samples from 417 women who underwent initial surgical debulking were stained with anti-CHFR antibody and scored in a blinded fashion. CHFR levels, expressed as a modified H-score, were examined for association with histology, grade, time to progression (TTP) and overall survival (OS). In addition, patient-derived xenografts from 69 ovarian carcinoma patients were examined for CHFR expression and sensitivity to paclitaxel monotherapy. In clinical ovarian cancer specimens, CHFR expression was positively associated with serous histology (p = 0.0048), higher grade (p = 0.000014) and higher stage (p = 0.016). After correction for stage and debulking, there was no significant association between CHFR staining and overall survival (p = 0.62) or time to progression (p = 0.91) in patients with high grade serous cancers treated with platinum/taxane chemotherapy (N = 249). Likewise, no association between CHFR expression and paclitaxel sensitivity was observed in ovarian cancer PDXs treated with paclitaxel monotherapy. Accordingly, differences in CHFR expression are unlikely to play a major role in paclitaxel sensitivity of high grade serous ovarian cancer.

Statistical analysis of comparative tumor growth repeated measures experiments in the ovarian cancer patient derived xenograft (PDX) setting.

Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling of tumor growth data. Biologically plausible structures for the covariation between repeated tumor burden measurements are explained. Graphical, tabular, and information criteria tools useful for choosing the mean model functional form and covariation structure are demonstrated in a Case Study of five PDX models comparing cancer treatments. Power calculations were performed via simulation. Linear mixed effects regression models applied to the natural log scale were shown to describe the observed data well. A straight growth function fit well for two PDX models. Three PDX models required quadratic or cubic polynomial (time squared or cubed) terms to describe delayed tumor regression or initial tumor growth followed by regression. Spatial(power), spatial(power) + RE, and RE covariance structures were found to be reasonable. Statistical power is shown as a function of sample size for different levels of variation. Linear mixed effects regression models provide a unified and flexible framework for analysis of PDX repeated measures data, use all available data, and allow estimation of tumor doubling time.

The humoral immune response to high-dose influenza vaccine in persons with monoclonal B-cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL).

BACKGROUND: Limited data are available regarding the immunogenicity of high-dose influenza vaccine among persons with chronic lymphocytic leukemia (CLL) and monoclonal B cell lymphocytosis (MBL). METHODS: A prospective pilot study of humoral immune responses to 2013-2014 and 2014-2015 high-dose trivalent influenza vaccine (HD IIV; Fluzone® High-Dose; Sanofi Pasteur) was conducted among individuals with MBL and previously untreated CLL. Serum hemagglutination inhibition (HAI) antibody titers were measured at baseline and Day 28 after vaccination; seroprotection and seroconversion rates were determined. Memory B cell responses were assessed by B-cell enzyme-linked immune absorbent spotassays. RESULTS: Thirty subjects (17 CLL and 13 MBL) were included. Median age was 69.5 years. Day 28 seroprotection rates for the cohort were 19/30 (63.3%) for A/H1N1; 21/23 (91.3%) for A/H3N2; and 13/30 (43.3%) for influenza B. Those with MBL achieved higher day 28 HAI geometric mean titers (54.1 [4.9, 600.1] vs. 12.1 [1.3, 110.1]; p = 0.01) and higher Day 28 seroprotection rates (76.9% vs. 17.6%; p = 0.002) against the influenza B-vaccine strain virus than those with CLL. CONCLUSIONS: Immunogenicity of the HD IIV3 in patients with CLL and MBL is lower than reported in healthy adults. Immunogenicity to influenza B was greater in those with MBL than CLL.

Co-expression patterns of chimeric antigen receptor (CAR)-T cell target antigens in primary and recurrent ovarian cancer.

OBJECTIVE: Chimeric antigen receptor (CAR)-T cell strategies ideally target a surface antigen that is exclusively and uniformly expressed by tumors; however, no such antigen is known for high-grade serous ovarian carcinoma (HGSC). A potential solution involves combinatorial antigen targeting with AND or OR logic-gating. Therefore, we investigated co-expression of CA125, Mesothelin (MSLN) and Folate Receptor alpha (FOLRA) on individual tumor cells in HGSC. METHODS: RNA expression of CA125, MSLN, and FOLR1 was assessed using TCGA (HGSC) and GTEx (healthy tissues) databases. Antigen expression profiles and CD3+, CD8+ and CD20+ tumor-infiltrating lymphocyte (TIL) patterns were assessed in primary and recurrent HGSC by multiplex immunofluorescence and immunohistochemistry. RESULTS: At the transcriptional level, each antigen was overexpressed in >90% of cases; however, MSLN and FOLR1 showed substantial expression in healthy tissues. At the protein level, CA125 was expressed by the highest proportion of cases and tumor cells per case, followed by MSLN and FOLRA. The most promising pairwise combination was CA125 and/or MSLN (OR gate), with 51.9% of cases containing ≥90% of tumor cells expressing one or both antigens. In contrast, only 5.8% of cases contained ≥90% of tumor cells co-expressing CA125 and MSLN (AND gate). Antigen expression patterns showed modest correlations with TIL. Recurrent tumors retained expression of all three antigens and showed increased TIL densities. CONCLUSIONS: An OR-gated CAR-T cell strategy against CA125 and MSLN would target the majority of tumor cells in most cases. Antigen expression and T-cell infiltration patterns are favorable for this strategy in primary and recurrent disease.

The DNA Cytosine Deaminase APOBEC3B is a Molecular Determinant of Platinum Responsiveness in Clear Cell Ovarian Cancer.

PURPOSE: Clear cell ovarian carcinoma (CCOC) is an aggressive disease that often demonstrates resistance to standard chemotherapies. Approximately 25% of patients with CCOC show a strong APOBEC mutation signature. Here, we determine which APOBEC3 enzymes are expressed in CCOC, establish clinical correlates, and identify a new biomarker for detection and intervention. EXPERIMENTAL DESIGNS: APOBEC3 expression was analyzed by IHC and qRT-PCR in a pilot set of CCOC specimens (n = 9 tumors). The IHC analysis of APOBEC3B was extended to a larger cohort to identify clinical correlates (n = 48). Dose-response experiments with platinum-based drugs in CCOC cell lines and carboplatin treatment of patient-derived xenografts (PDXs) were done to address mechanistic linkages. RESULTS: One DNA deaminase, APOBEC3B, is overexpressed in a formidable subset of CCOC tumors and is low or absent in normal ovarian and fallopian tube epithelial tissues. High APOBEC3B expression associates with improved progression-free survival (P = 0.026) and moderately with overall survival (P = 0.057). Cell-based studies link APOBEC3B activity and subsequent uracil processing to sensitivity to cisplatin and carboplatin. PDX studies extend this mechanistic relationship to CCOC tissues. CONCLUSIONS: These studies demonstrate that APOBEC3B is overexpressed in a subset of CCOC and, contrary to initial expectations, associated with improved (not worse) clinical outcomes. A likely molecular explanation is that APOBEC3B-induced DNA damage sensitizes cells to additional genotoxic stress by cisplatin. Thus, APOBEC3B is a molecular determinant and a candidate predictive biomarker of the therapeutic response to platinum-based chemotherapy. These findings may have broader translational relevance, as APOBEC3B is overexpressed in many different cancer types.

53BP1 as a potential predictor of response in PARP inhibitor-treated homologous recombination-deficient ovarian cancer.

OBJECTIVE: Poly(ADP-ribose) polymerase (PARP) inhibitors have shown substantial activity in homologous recombination- (HR-) deficient ovarian cancer and are undergoing testing in other HR-deficient tumors. For reasons that are incompletely understood, not all patients with HR-deficient cancers respond to these agents. Preclinical studies have demonstrated that changes in alternative DNA repair pathways affect PARP inhibitor (PARPi) sensitivity in ovarian cancer models. This has not previously been assessed in the clinical setting. METHODS: Clonogenic and plasmid-based HR repair assays were performed to compare BRCA1-mutant COV362 ovarian cancer cells with or without 53BP1 gene deletion. Archival biopsies from ovarian cancer patients in the phase I, open-label clinical trial of PARPi ABT-767 were stained for PARP1, RAD51, 53BP1 and multiple components of the nonhomologous end-joining (NHEJ) DNA repair pathway. Modified histochemistry- (H-) scores were determined for each repair protein in each sample. HRD score was determined from tumor DNA. RESULTS: 53BP1 deletion increased HR in BRCA1-mutant COV362 cells and decreased PARPi sensitivity in vitro. In 36 women with relapsed ovarian cancer, responses to the PARPi ABT-767 were observed exclusively in cancers with HR deficiency. In this subset, 7 of 18 patients (39%) had objective responses. The actual HRD score did not further correlate with change from baseline tumor volume (r = 0.050; p = 0.87). However, in the HR-deficient subset, decreased 53BP1 H-score was associated with decreased antitumor efficacy of ABT-767 (r = -0.69, p = 0.004). CONCLUSION: Differences in complementary repair pathways, particularly 53BP1, correlate with PARPi response of HR-deficient ovarian cancers.

EGFR as a prognostic biomarker and therapeutic target in ovarian cancer: evaluation of patient cohort and literature review.

BACKGROUND: Limited effectiveness of therapeutic agents targeting epidermal growth factor receptor (EGFR) in clinical trials using unselected ovarian cancer patients has prompted efforts to more effectively stratify patients who might best benefit from these therapies. A series of studies that have evaluated immunohistochemical (IHC) staining of EGFR in ovarian cancer biopsies has produced unclear results as to the utility of this measure as a prognostic biomarker. Here, we used one of the largest, single institution cohorts to date to determine possible associations of EGFR expression with patient outcome. METHODS: We performed IHC staining of EGFR in tissue microarrays including nearly 500 patient tumor samples. Staining was classified by subcellular localization (membranous, cytoplasmic) or by automated image analysis algorithms. We also performed a literature review to place these results in the context of previous studies. RESULTS: No significant associations were found between EGFR subcellular localization or expression and histology, stage, grade, or outcome. These results were broadly consistent with the consensus of the reviewed literature. CONCLUSIONS: These results suggest that IHC staining for EGFR may not be a useful prognostic biomarker for ovarian cancer patients. Future studies should pursue other staining methods or analysis in combination with other pathway mediators.

Serine protease inhibitor Kazal type 1 (SPINK1) drives proliferation and anoikis resistance in a subset of ovarian cancers.

Ovarian cancer represents the most lethal tumor type among malignancies of the female reproductive system. Overall survival rates remain low. In this study, we identify the serine protease inhibitor Kazal type 1 (SPINK1) as a potential therapeutic target for a subset of ovarian cancers. We show that SPINK1 drives ovarian cancer cell proliferation through activation of epidermal growth factor receptor (EGFR) signaling, and that SPINK1 promotes resistance to anoikis through a distinct mechanism involving protease inhibition. In analyses of ovarian tumor specimens from a Mayo Clinic cohort of 490 patients, we further find that SPINK1 immunostaining represents an independent prognostic factor for poor survival, with the strongest association in patients with nonserous histological tumor subtypes (endometrioid, clear cell, and mucinous). This study provides novel insight into the fundamental processes underlying ovarian cancer progression, and also suggests new avenues for development of molecularly targeted therapies.

Assessment of published models and prognostic variables in epithelial ovarian cancer at Mayo Clinic.

OBJECTIVES: Epithelial ovarian cancer (EOC) is an aggressive disease in which first line therapy consists of a surgical staging/debulking procedure and platinum based chemotherapy. There is significant interest in clinically applicable, easy to use prognostic tools to estimate risk of recurrence and overall survival. In this study we used a large prospectively collected cohort of women with EOC to validate currently published models and assess prognostic variables. METHODS: Women with invasive ovarian, peritoneal, or fallopian tube cancer diagnosed between 2000 and 2011 and prospectively enrolled into the Mayo Clinic Ovarian Cancer registry were identified. Demographics and known prognostic markers as well as epidemiologic exposure variables were abstracted from the medical record and collected via questionnaire. Six previously published models of overall and recurrence-free survival were assessed for external validity. In addition, predictors of outcome were assessed in our dataset. RESULTS: Previously published models validated with a range of c-statistics (0.587-0.827), though application of models containing variables which are not part of routine practice were somewhat limited by missing data; utilization of all applicable models and comparison of results are suggested. Examination of prognostic variables identified only the presence of ascites and ASA score to be independent predictors of prognosis in our dataset, albeit with marginal gain in prognostic information, after accounting for stage and debulking. CONCLUSIONS: Existing prognostic models for newly diagnosed EOC showed acceptable calibration in our cohort for clinical application. However, modeling of prospective variables in our dataset reiterates that stage and debulking remains the most important predictors of prognosis in this setting.

Large-scale evaluation of common variation in regulatory T cell-related genes and ovarian cancer outcome.

The presence of regulatory T cells (Treg) in solid tumors is known to play a role in patient survival in ovarian cancer and other malignancies. We assessed inherited genetic variations via 749 tag single-nucleotide polymorphisms (SNP) in 25 Treg-associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. We analyzed genotype and overall survival in 10,084 women with invasive epithelial ovarian cancer, including 5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous carcinoma cases of European descent across 28 studies from the Ovarian Cancer Association Consortium (OCAC). The strongest associations were found for endometrioid carcinoma and IL2RA SNPs rs11256497 [HR, 1.42; 95% confidence interval (CI), 1.22-1.64; P = 5.7 × 10(-6)], rs791587 (HR, 1.36; 95% CI, 1.17-1.57; P = 6.2 × 10(-5)), rs2476491 (HR, = 1.40; 95% CI, 1.19-1.64; P = 5.6 × 10(-5)), and rs10795763 (HR, 1.35; 95% CI, 1.17-1.57; P = 7.9 × 10(-5)), and for clear cell carcinoma and CTLA4 SNP rs231775 (HR, 0.67; 95% CI, 0.54-0.82; P = 9.3 × 10(-5)) after adjustment for age, study site, population stratification, stage, grade, and oral contraceptive use. The rs231775 allele associated with improved survival in our study also results in an amino acid change in CTLA4 and previously has been reported to be associated with autoimmune conditions. Thus, we found evidence that SNPs in genes related to Tregs seem to play a role in ovarian cancer survival, particularly in patients with clear cell and endometrioid epithelial ovarian cancer.

Utility of progranulin and serum leukocyte protease inhibitor as diagnostic and prognostic biomarkers in ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer-related death in females and leading gynecologic cause of cancer-related death. Despite the identification of a number of serum biomarkers, methods to identify early-stage disease and predict prognosis remain scarce. We have evaluated two biologically connected serum biomarkers, serum leukocyte protease inhibitor (SLPI) and progranulin (PGRN). METHODS: Two-hundred frozen plasma samples were acquired from the Mayo Clinic Biospecimen Repository for Ovarian Cancer Research. Samples were obtained from 50 patients with benign conditions, 50 with American Joint Committee on Cancer (AJCC) stage I and II EOC, and 100 with AJCC stage III and IV EOC. Samples were obtained before surgical resection of a mass and were analyzed for absolute levels of SLPI and PGRN using ELISA assays. Receiver-operator characteristic curves were generated for SLPI and PGRN. Median follow-up was 48 months. RESULTS: Absolute levels of SLPI were significantly elevated in patients with EOC compared with benign disease and predicted the presence of EOC (AUC of 0.812; P = 0.04); SLPI remained elevated in the subset of patients with normal CA-125. PGRN levels were not significantly increased in patients with early-stage or late-stage EOC as a whole, but an increase in PGRN levels was associated with decreased overall survival in advanced EOC. CONCLUSIONS: SLPI levels are elevated in EOC, and SLPI shows promise as a diagnostic biomarker for patients with both elevated and normal CA-125 levels. An increase in PGRN is associated with decreased overall survival. IMPACT: SLPI is elevated in EOC and warrants investigation in a screening study in women at risk for EOC.