Anti-Inflammatory Drug Use and Ovarian Cancer Risk by COX1/COX2 Expression and Infiltration of Tumor-Associated Macrophages

Associations between prediagnostic aspirin use and ovarian tumor gene expression

BACKGROUND

Aspirin use has been associated with reduced ovarian cancer risk, yet the underlying biological mechanisms are not fully understood. To gain mechanistic insights, we assessed the association between prediagnosis low and regular-dose aspirin use and gene expression profiles in ovarian tumors.

METHODS

RNA sequencing was performed on high-grade serous, poorly differentiated, and high-grade endometrioid ovarian cancer tumors from the Nurses' Health Study (NHS), NHSII, and New England Case-Control Study (n = 92 cases for low, 153 cases for regular-dose aspirin). Linear regression identified differentially expressed genes associated with aspirin use, adjusted for birth decade and cohort. False discovery rates (FDR) were used to account for multiple testing and gene set enrichment analysis was used to identify biological pathways.

RESULTS

No individual genes were significantly differentially expressed in ovarian tumors in low or regular-dose aspirin users accounting for multiple comparisons. However, current versus never use of low-dose aspirin was associated with upregulation of immune pathways (e.g., allograft rejection, FDR = 5.8 × 10-10 ; interferon-gamma response, FDR = 2.0 × 10-4 ) and downregulation of estrogen response pathways (e.g., estrogen response late, FDR = 4.9 × 10-8 ). Ovarian tumors from current regular aspirin users versus never users were also associated with upregulation in interferon pathways (FDR <1.5 × 10-4 ) and downregulation of multiple extracellular matrix (ECM) architecture pathways (e.g., ECM organization, 4.7 × 10-8 ).

CONCLUSION

Our results suggest low and regular-dose aspirin may impair ovarian tumorigenesis in part via enhancing adaptive immune response and decreasing metastatic potential supporting the likely differential effects on ovarian carcinogenesis and progression by dose of aspirin.

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.

The role of lipid metabolic reprogramming in tumor microenvironment

Metabolic reprogramming is one of the most important hallmarks of malignant tumors. Specifically, lipid metabolic reprogramming has marked impacts on cancer progression and therapeutic response by remodeling the tumor microenvironment (TME). In the past few decades, immunotherapy has revolutionized the treatment landscape for advanced cancers. Lipid metabolic reprogramming plays pivotal role in regulating the immune microenvironment and response to cancer immunotherapy. Here, we systematically reviewed the characteristics, mechanism, and role of lipid metabolic reprogramming in tumor and immune cells in the TME, appraised the effects of various cell death modes (specifically ferroptosis) on lipid metabolism, and summarized the antitumor therapies targeting lipid metabolism. Overall, lipid metabolic reprogramming has profound effects on cancer immunotherapy by regulating the immune microenvironment; therefore, targeting lipid metabolic reprogramming may lead to the development of innovative clinical applications including sensitizing immunotherapy.

Role of p53 methylation in manganese-induced cyclooxygenase-2 expression in BV2 microglial cells

Manganese (Mn) is an essential cofactor for many enzymes and plays an important role in normal growth and development. However, excess exposure to manganese (Mn) may be an important environmental factor leading to neurodegeneration. The overexpression of microglial cyclooxygenase-2 (COX-2) plays a key role in neuroinflammation in neurodegenerative diseases. The existing data suggest that Mn can induce neuroinflammation by up-regulating COX-2 expression. However, the mechanisms involved in Mn-induced microglial COX-2 up-regulation remain to be determined. The aim of this study was to investigate the role of p53 in Mn-induced COX-2 expression in microglial cells. The results showed that Mn exposure induced the up-regulation of COX-2 and inhibited the expression of p53 in BV2 microglial cells. The addition of p53 activator and the over-expression of p53 blocked the expression of COX-2 and prostaglandin E2 (PGE2), a COX-2 downstream effector, induced by Mn. Further, Mn increased the methylation of p53 DNA in microglia, while the addition of demethylation reagent 5-Aza-dC enhanced the expression of p53 but decreased the expression of COX-2. These results suggested that Mn may inhibit p53 expression through induction of DNA methylation, which can further induce the expression of COX-2 in microglial cells.

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.

NSAIDs: Old Acquaintance in the Pipeline for Cancer Treatment and Prevention─Structural Modulation, Mechanisms of Action, and Bright Future

The limitations of current chemotherapeutic drugs are still a major issue in cancer treatment. Thus, targeted multimodal therapeutic approaches need to be strategically developed to successfully control tumor growth and prevent metastatic burden. Inflammation has long been recognized as a hallmark of cancer and plays a key role in the tumorigenesis and progression of the disease. Several epidemiological, clinical, and preclinical studies have shown that traditional nonsteroidal anti-inflammatory drugs (NSAIDs) exhibit anticancer activities. This Perspective reports the most recent outcomes for the treatment and prevention of different types of cancers for several NSAIDs alone or in combination with current chemotherapeutic drugs. Furthermore, an extensive review of the most promising structural modifications is reported, such as phospho, H₂S, and NO releasing-, selenium-, metal complex-, and natural product-NSAIDs, among others. We also provide a perspective about the new strategies used to obtain more efficient NSAID- or NSAID derivative- formulations for targeted delivery.

Joint IARC/NCI International Cancer Seminar Series Report: expert consensus on future directions for ovarian carcinoma research

Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer and the United States National Cancer Institute jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic and prognostic research on ovarian carcinoma.

Prospective Analyses of Lifestyle Factors Related to Energy Balance and Ovarian Cancer Risk by Infiltration of Tumor-Associated Macrophages

BACKGROUND

Lifestyle factors related to energy balance have been associated with ovarian cancer risk and influence the tumor immune microenvironment, including tumor-associated macrophages (TAM). However, no studies have assessed whether these factors differentially impact ovarian cancer risk by TAM densities.

METHODS

We conducted a prospective analysis in the Nurses' Health Studies to examine the associations of physical activity, sitting time, and a food-based empirical dietary inflammatory pattern (EDIP) score with invasive epithelial ovarian cancer risk by TAM density assessed by immunohistochemistry. We considered density of CD68 (marker of total TAMs) and CD163 (marker of pro-carcinogenic M2-type TAMs), and their ratios. We used multivariable Cox proportional hazards regression to calculate hazard ratios (HR) and 95% confidence intervals (CI) of exposures with risk of ovarian tumors with high versus low TAMs, including analyses stratified by body mass index.

RESULTS

Analyses included 312 incident ovarian cancer cases with TAM measurements. Physical activity, sitting time, and EDIP score were not differentially associated with ovarian cancer risk by TAM densities (P heterogeneity > 0.05). Among overweight and obese women, higher EDIP score was associated with increased risk of CD163 low-density tumors (HR comparing extreme tertiles, 1.57; 95% CI, 0.88-2.80; P trend = 0.01), but not CD163 high-density tumors (comparable HR, 1.16; 95% CI, 0.73-1.86; P trend = 0.24), though this difference was not statistically significant (P heterogeneity = 0.22).

CONCLUSIONS

We did not observe differential associations between lifestyle factors and ovarian cancer risk by TAM densities.

IMPACT

Future investigations examining the interplay between other ovarian cancer risk factors and the tumor immune microenvironment may help provide insight into ovarian cancer etiology.

Ferroptosis-Related Gene Model to Predict Overall Survival of Ovarian Carcinoma

Background

Ovarian cancer (OC) is the eighth most common cause of cancer death and the second cause of gynecologic cancer death in women around the world. Ferroptosis, an iron-dependent regulated cell death, plays a vital role in the development of many cancers. Applying expression of ferroptosis-related gene to forecast the cancer progression is helpful for cancer treatment. However, the relationship between ferroptosis-related genes and OC patient prognosis is still vastly unknown, making it still a challenge for developing ferroptosis therapy for OC.

Methods

The Cancer Genome Atlas (TCGA) data of OC were obtained and the datasets were randomly divided into training and test datasets. A novel ferroptosis-related gene signature associated with overall survival (OS) was constructed according to the training cohort. The test dataset and ICGC dataset were used to validate this signature.

Results

We constructed a model containing nine ferroptosis-related genes, namely, LPCAT3, ACSL3, CRYAB, PTGS2, ALOX12, HSBP1, SLC1A5, SLC7A11, and ZEB1, and predicted the OS of OC in TCGA. At a suitable cutoff, patients were divided into low risk and high risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics (ROCs) were as high as 0.664, respectively. Then, the test dataset and the ICGC dataset were used to evaluate our model, and the ROCs of test dataset were 0.667 and 0.777, respectively. In addition, functional analysis and correlation analysis showed that immune-related pathways were significantly enriched. Meanwhile, we also integrated with other clinical factors and we found the synthesized clinical factors and ferroptosis-related gene signature improved prognostic accuracy relative to the ferroptosis-related gene signature alone.

Conclusion

The ferroptosis-related gene signature could predict the OS of OC patients and improve therapeutic decision-making.

Dexamethasone induces aberrant macrophage immune function and apoptosis

Glucocorticoids (GCs) are known potent clinical drugs, however, their mode of action is still complex and debatable. Macrophages are the most important target of GCs and play a key role in tumor immunity in vivo, but their relationship is also controversial. In the present study, the lentivirus system was used to overexpress and knock down the level of transcription factor Krüppel-like factor 9 (KLF9). The results revealed that dexamethasone (Dex) induced ROS generation and mitochondria-dependent apoptosis in RAW 264.7 cells via the KLF9. In addition, overexpression of KLF9 significantly increased apoptosis of RAW 264.7 cells. Notably, ELISA assay revealed that increased expression of KLF9 inhibited LPS-induced COX-2 expression and reduced COX-2-derived prostaglandin E2 and pro-inflammatory cytokine secretion. Furthermore, a co-culture system was used to reveal that overexpression of KLF9 in RAW 264.7 cells promoted HepG2 cell survival. In summary, it is reported that KLF9 promoted apoptosis of proinflammatory macrophages, and suppressed the antitumor effects, which can be selectively targeted by GCs as a novel mechanism to suppress antineoplastic activity.

Urinary PGE-M Levels and Risk of Ovarian Cancer

BACKGROUND

Regular aspirin use may lower ovarian cancer risk by blocking the cyclooxygenase enzymes, resulting in lower expression of prostaglandins, including prostaglandin E2 (PGE2). We evaluated whether higher prediagnosis PGE-M (a urinary biomarker of PGE2) was associated with increased ovarian cancer risk in three prospective cohorts.

METHODS

We conducted a case-control study nested in the Nurses' Health Study (NHS), NHSII, and Shanghai Women's Health Study. Our analyses included 304 cases of epithelial ovarian cancer diagnosed from 1996 to 2015 and 600 matched controls. We measured urinary PGE-M using LC/MS with normalization to creatinine. Measures from each study were recalibrated to a common standard. We estimated ORs and 95% confidence intervals (CI) using conditional logistic regression, with PGE-M levels modeled in quartiles. Multivariable models were adjusted for ovarian cancer risk factors.

RESULTS

There was no evidence of an association between urinary PGE-M levels and ovarian cancer risk for women with PGE-M levels in the top versus bottom quartile (OR = 0.80; 95% CI, 0.51-1.27; P trend = 0.37). We did not observe heterogeneity by histotype (P = 0.53), and there was no evidence of effect modification by body mass index (P interaction = 0.82), aspirin use (P interaction = 0.59), or smoking (P interaction = 0.14).

CONCLUSIONS

Prediagnosis urinary PGE-M levels were not significantly associated with ovarian cancer risk. Larger sample sizes are needed to consider a more modest association and to evaluate associations for specific tumor subtypes.

IMPACT

Systemic prostaglandin levels do not appear strongly associated with ovarian cancer risk. Future research into aspirin use and ovarian cancer risk should consider local prostaglandins and prostaglandin-independent mechanisms.