The temporal trend of women's cancer in Changle, China and a migrant epidemiological study.

Background: Although the etiology of women's cancer has been extensively studied in the last few decades, there is still little evidence comparing the temporal pattern of these cancers among different populations. Methods: Cancer incidence and mortality data from 1988 to 2015 were extracted from the Changle Cancer Register in China, and cancer incidence data for Los Angeles were extracted from Cancer Incidence in Five Continents plus database. A Joinpoint regression model was used to analyze the temporal trends of incidence and mortality for breast, cervical, corpus uteri and ovarian cancers. The standardized incidence ratios were applied to compare the cancer risk across populations. Results: An increasing trend of incidence rate for breast, cervical, corpus uteri and ovarian cancer was observed in Changle, although the rate leveled off for breast and cervical cancer after 2010, although not statistically significant. The mortality rate of breast and ovarian cancer was slightly increased during this period, while we found a decreased mortality of cervical cancer from 2010. The mortality of corpus uteri cancer showed a decreasing and then increasing trend. The incidence of breast, corpus uteri and ovarian cancer in Chinese American immigrants in Los Angeles was significantly higher than indigenous Changle Chinese and lower than Los Angeles whites. However, the incidence of cervical cancer in Chinese American immigrants shifted from significantly exceeding to lower than Changle Chinese. Conclusion: The incidence and mortality of women's cancers in Changle were generally on the rise, and this study concluded that environmental changes were important factors affecting the occurrence of these cancers. Appropriate preventive measures should be taken to control the occurrence of women's cancers by addressing different influencing factors.

Genetic and lifestyle factors for breast cancer risk assessment in Southeast China.

BACKGROUND: Despite the rising incidence and mortality of breast cancer among women in China, there are currently few predictive models for breast cancer in the Chinese population and with low accuracy. This study aimed to identify major genetic and life-style risk factors in a Chinese population for potential application in risk assessment models. METHODS: A case-control study in southeast China was conducted including 1321 breast cancer patients and 2045 controls during 2013-2016, in which the data were randomly divided into a training set and a test set on a 7:3 scale. The association between genetic and life-style factors and breast cancer was examined using logistic regression models. Using AUC curves, we also compared the performance of the logistic model to machine learning models, namely LASSO regression model and support vector machine (SVM), and the scores calculated from CKB, Gail and Tyrer-Cuzick models in the test set. RESULTS: Among all factors considered, the best model was achieved when polygenetic risk score, lifestyle, and reproductive factors were considered jointly in the logistic regression model (AUC = 0.73; 95% CI: 0.70-0.77). The models created in this study performed better than those using scores calculated from the CKB, Gail, and Tyrer-Cuzick models. However, the logistic model and machine learning models did not significantly differ from one another. CONCLUSION: In summary, we have found genetic and lifestyle risk predictors for breast cancer with moderate discrimination, which might provide reference for breast cancer screening in southeast China. Further population-based studies are needed to validate the model for future applications in personalized breast cancer screening programs.

The association between plasma chemokines and breast cancer risk and prognosis: A mendelian randomization study.

Background: Despite the potential role of several chemokines in the migration of cytotoxic immune cells to prohibit breast cancer cell proliferation, a comprehensive view of chemokines and the risk and prognosis of breast cancer is scarce, and little is known about their causal associations. Methods: With a two-sample Mendelian randomization (MR) approach, genetic instruments associated with 30 plasma chemokines were created. Their genetic associations with breast cancer and its survival by molecular subtypes were extracted from the recent genome-wide association study of 133,384 breast cancer cases and 113,789 controls, with available survival information for 96,661 patients. We further tested the associations between the polygenic risk score (PRS) for chemokines and breast cancer in the UK Biobank cohort using logistic regression models, while the association with breast cancer survival was tested using Cox regression models. In addition, the association between chemokine expression in tumors and breast cancer survival was also analyzed in the TCGA cohort using Cox regression models. Results: Plasma CCL5 was causally associated with breast cancer in the MR analysis, which was significant in the luminal and HER-2 enriched subtypes and further confirmed using PRS analysis (OR = 0.94, 95% CI = 0.89-1.00). A potential causal association with breast cancer survival was only found for plasma CCL19, especially for ER-positive patients. Although not replicated in the UK Biobank, we still found an inverse association between CCL19 expression in tumors and breast cancer overall and relapse-free survival in the TCGA cohort (HR = 0.58, 95% CI = 0.35-0.95). Conclusion: We observed an inverse association between genetic predisposition to CCL5 and breast cancer, while CCL19 was associated with breast cancer survival. These associations suggested the potential of these chemokines as tools for breast cancer prevention and treatment.