Lifestyle and Reproductive Factors and Ovarian Cancer Risk by p53 and MAPK Expression

Predictors of residual disease after debulking surgery in advanced stage ovarian cancer

Objective

Optimal debulking with no macroscopic residual disease strongly predicts ovarian cancer survival. The ability to predict likelihood of optimal debulking, which may be partially dependent on tumor biology, could inform clinical decision-making regarding use of neoadjuvant chemotherapy. Thus, we developed a prediction model including epidemiological factors and tumor markers of residual disease after primary debulking surgery.

Methods

Univariate analyses examined associations of 11 pre-diagnosis epidemiologic factors (n=593) and 24 tumor markers (n=204) with debulking status among incident, high-stage, epithelial ovarian cancer cases from the Nurses' Health Studies and New England Case Control study. We used Bayesian model averaging (BMA) to develop prediction models of optimal debulking with 5x5-fold cross-validation and calculated the area under the curve (AUC).

Results

Current aspirin use was associated with lower odds of optimal debulking compared to never use (OR=0.52, 95%CI=0.31-0.86) and two tissue markers, ADRB2 (OR=2.21, 95%CI=1.23-4.41) and FAP (OR=1.91, 95%CI=1.24-3.05) were associated with increased odds of optimal debulking. The BMA selected aspirin, parity, and menopausal status as the epidemiologic/clinical predictors with the posterior effect probability ≥20%. While the prediction model with epidemiologic/clinical predictors had low performance (average AUC=0.49), the model adding tissue biomarkers showed improved, but weak, performance (average AUC=0.62).

Conclusions

Addition of ovarian tumor tissue markers to our multivariable prediction models based on epidemiologic/clinical data slightly improved the model performance, suggesting debulking status may be in part driven by tumor characteristics. Larger studies are warranted to identify those at high risk of poor surgical outcomes informing personalized treatment.

Anticancer Effect of Puerarin on Ovarian Cancer Progression Contributes to the Tumor Suppressor Gene Expression and Gut Microbiota Modulation

Ovarian cancer (OC) causes more deaths than any other cancer of the female reproductive system due to its late presentation and malignant nature. Although significant progress has been made in the diagnosis and treatment of OC over the last decade, chemotherapeutic drug resistance and cancer recurrence remain serious challenges in OC management. In the field of cancer therapy, traditional Chinese herbal medicines and their active compounds have been widely reported to have favorable therapeutic effects on cancer. Recent studies have also revealed the protective effect of puerarin in cancer, but the exact role and underlying mechanism of puerarin in OC remain unclear. Here, we established in vivo and in vitro OC models to evaluate the anticancer effect of puerarin. It was found that puerarin significantly inhibited OC cell viability and proliferation and induced cell apoptosis. In OC model mice, puerarin treatment suppressed tumor formation and modulated the gut microbiome. In addition, the expression of tumor suppressor genes was activated by puerarin in vitro and in vivo. These findings add to the existing knowledge on the usefulness of herbal active ingredients for the prevention and treatment of OC and provide a new perspective regarding the therapeutic potential of puerarin in cancer.

Lifetime ovulatory years and ovarian cancer gene expression profiles

BACKGROUND

Greater ovulatory years is associated with increased ovarian cancer risk. Although ovulation leads to an acute pro-inflammatory local environment, how long-term exposure to ovulation impacts ovarian carcinogenesis is not fully understood. Thus, we examined the association between gene expression profiles of ovarian tumors and lifetime ovulatory years to enhance understanding of associated biological pathways.

METHODS

RNA sequencing data was generated on 234 invasive ovarian cancer tumors that were high-grade serous, poorly differentiated, or high-grade endometrioid from the Nurses' Health Study (NHS), NHSII, and the New England Case Control Study. We used linear regression to identify differentially expressed genes by estimated ovulatory years, adjusted for birth decade and cohort, overall and stratified by menopausal status at diagnosis. We used false discovery rates (FDR) to account for multiple testing. Gene set enrichment analysis (GSEA) with Cancer Hallmarks, KEGG, and Reactome databases was used to identify biological pathways associated with ovulatory years.

RESULTS

No individual genes were significantly differentially expressed by ovulatory years (FDR > 0.19). However, GSEA identified several pathways that were significantly associated with ovulatory years, including downregulation of pathways related to inflammation and proliferation (FDR < 1.0 × 10-5). Greater ovulatory years were more strongly associated with downregulation of genes related to proliferation (e.g., E2F targets, FDR = 1.53 × 10-24; G2M checkpoints, FDR = 3.50 × 10-22) among premenopausal versus postmenopausal women at diagnosis. The association of greater ovulatory years with downregulation of genes involved in inflammatory response such as interferon gamma response pathways (FDR = 7.81 × 10-17) was stronger in postmenopausal women.

CONCLUSIONS

Our results provide novel insight into the biological pathways that link ovulatory years to ovarian carcinogenesis, which may lead to development of targeted prevention strategies for ovarian cancer.

Obesity and gynecological cancers: A toxic relationship

Despite the evidence supporting the relevance of obesity and obesity‐associated disorders in the development, management, and prognosis of various cancers, obesity rates continue to increase worldwide. Growing evidence supports the involvement of obesity in the development of gynecologic malignancies. This article explores the molecular basis governing the alteration of hallmarks of cancer in the development of obesity‐related gynecologic malignancies encompassing cervical, endometrial, and ovarian cancers. We highlight specific examples of how development, management, and prognosis are affected for each cancer, incorporate current knowledge on complementary approaches including lifestyle interventions to improve patient outcomes, and highlight how new technologies are helping us better understand the biology underlying this neglected pandemic.

This review focuses on how obesity impacts cancer hallmarks in gynecologic malignancies, thus affecting the diagnosis, management, treatment, and prognosis of these diseases.

Review of Mendelian Randomization Studies on Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest gynecological cancers worldwide. Previous observational epidemiological studies have revealed associations between modifiable environmental risk factors and OC risk. However, these studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) analysis has been established as a reliable method to investigate the causal relationship between risk factors and diseases using genetic variants to proxy modifiable exposures. Over recent years, MR analysis in OC research has received extensive attention, providing valuable insights into the etiology of OC as well as holding promise for identifying potential therapeutic interventions. This review provides a comprehensive overview of the key principles and assumptions of MR analysis. Published MR studies focusing on the causality between different risk factors and OC risk are summarized, along with comprehensive analysis of the method and its future applications. The results of MR studies on OC showed that higher BMI and height, earlier age at menarche, endometriosis, schizophrenia, and higher circulating β-carotene and circulating zinc levels are associated with an increased risk of OC. In contrast, polycystic ovary syndrome; vitiligo; higher circulating vitamin D, magnesium, and testosterone levels; and HMG-CoA reductase inhibition are associated with a reduced risk of OC. MR analysis presents a2 valuable approach to understanding the causality between different risk factors and OC after full consideration of its inherent assumptions and limitations.

Clinicopathological and epidemiological significance of breast cancer subtype reclassification based on p53 immunohistochemical expression

TP53 mutations are common in breast cancer and are typically associated with more aggressive tumor characteristics, but little is known about the clinicopathological and epidemiological relevance of p53 protein expression, a TP53 mutation surrogate, in breast cancer subtypes. In this study of 7226 Chinese women with invasive breast cancer, we defined breast cancer subtypes using immunohistochemical (IHC) measures of hormone receptors and HER2 in conjunction with histologic grade. p53 expression status was then used to further stratify subtypes into p53-positive and p53-negative. Odds ratios (ORs) and 95% confidence intervals (CIs) in case-only logistic regression analyses were used to examine heterogeneity across different subtypes. The frequency of p53 protein expression varied by breast cancer subtype, being lowest in the luminal A-like and highest in the triple-negative and HER2-enriched subtypes (P-value < 0.01). In luminal A-like and B-like/HER2-negative subtypes, p53 positivity was associated with early-onset tumors, high grade, high proliferative index, and basal marker (CK5/6 and EGFR) expression. Further, compared with luminal A-like/p53-negative patients, A-like/p53-positive patients were more likely to be parous [adjusted OR parous vs. nulliparous = 2.67 (1.60, 4.51); P-value < 0.01] and to have breastfed [adjusted OR ever vs. never = 1.38 (1.03, 1.85); P-value = 0.03]. p53 positivity was not associated with examined clinical and risk factors in other tumor subtypes. Overall, these findings suggest that p53 expression, which is readily available in many settings, can be used to identify phenotypes of luminal A-like breast cancer with distinct clinical and epidemiological implications.