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Heng-Ming Ye,1 Min-Jie Lu,1 Qiang Liu,2 Ying Lin,3 Lu-Ying Tang,4 Ze-Fang Ren1 1The School of Public Health, Sun Yat-sen University, Guangzhou, 510080, People’s Republic of China; 2Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, People’s Republic of China; 3The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People’s Republic of China; 4The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510630, People’s Republic of ChinaCorrespondence: Ze-Fang Ren, The School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou, 510080, People’s Republic of China, Tel/Fax +86-20-87332577, Email renzef@mail.sysu.edu.cnBackground: Animal experiments have shown the anticancer activity of Toxoplasma gondii (T. gondii), but its effect on the prognosis of cancer patients is unclear. Thus, the present study aimed to investigate the prognostic role of anti-T. gondii IgG in breast cancer patients and the modification effect of cytokines.Methods: A total of 1121 breast cancer patients were recruited between 2008 and 2018 and followed up until December 31, 2021. Anti-T. gondii IgG and cytokines were measured using an enzyme-linked immunosorbent assay (ELISA) kit and a multiplex assay platform. Endpoints were overall survival (OS) and progression-free survival (PFS). Survival and multiplicative interaction analyses were performed using multivariate Cox regression models.Results: According to the cutoff value of optical density (OD=0.111), 900 (80.29%) and 221 (19.71%) patients were divided into two groups: low or high anti-T. gondii IgG. Compared to patients with a low anti-T. gondii IgG level, the adjusted hazard ratios (HRs) of OS and PFS for patients with high anti-T. gondii IgG levels were 0.60 (95% confidence interval (CI): 0.37– 0.99) and 0.67 (0.46– 0.98), respectively. These associations were profound among patients with a high cytokine score (HR=0.29, 95% CI: 0.10– 0.82 for OS; HR=0.30

Yue-Yu Shi,1 Xing-Lei Chen,1 Qian-Xin Chen,1 Yuan-Zhong Yang,2 Meng Zhou,1 Yue-Xiang Ren,3 Lu-Ying Tang,3 Ze-Fang Ren1 1School of Public Health, Sun Yat-sen University, Guangzhou, People’s Republic of China; 2The Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China; 3The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of ChinaCorrespondence: Ze-Fang Ren, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou, Guangdong, People’s Republic of China, Tel/Fax +86-20-87332577, Email renzef@mail.sysu.edu.cn Lu-Ying Tang, The Third Affiliated Hospital, Sun Yat-sen University, 600 Tianhe Road, Guangzhou, Guangdong, People’s Republic of China, Tel +86-20-85253000, Fax +86-20-85253336, Email tangly@mail.sysu.edu.cnPurpose: Enolase-1 (ENO1) plays a key role in malignancies. Previous studies on the association between ENO1 expression and breast cancer prognosis had yielded inconsistent results. In the present study, we assessed the prognostic effect of ENO1 in breast cancer using Guangzhou Breast Cancer Study (GZBCS) cohort with full consideration of the potential confounders and the modification effects. The results were further validated in the TCGA-BRCA cohort and explained by tumor immunity.Methods: ENO1 protein expressions were evaluated by immunohistochemistry in tissue microarrays from 961 patients with primary invasive breast cancer. Chi-square tests were used to assess the association of ENO1 levels with the patient’s characteristics. Cox regression models were applied to assess the prognostic effects. The TCGA-BRCA cohort was utilized to validate the results and explore the potential mechanisms. The immune infiltration was determined using the CIBERSORT and ssGSEA algorithms; the correlation between ENO1 expression and the abundance of tumor-infiltrating immune cells (TIICs) and scores of immune-related functions was evaluated by Wilcoxon signed-rank tests and Spearman’s ra

Background: The etiology of colorectal cancer is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 > 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini-Hochberg FDR (BH-FDR) < 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10-8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR < 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10-11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het < 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer. Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact: The identified metabolites could be developed