Hongbing Shen

Characterization of metabolic perturbation prior to hepatocellular carcinoma (HCC) may deepen the understanding of causal pathways and identify novel biomarkers for early prevention. We conducted two 1:1 matched nested case-control studies (108 and 55 pairs) to examine the association of plasma metabolome (profiled using LC-MS) with the risk of HCC based on two prospective cohorts in China. Differential metabolites were identified by paired t tests and orthogonal partial least-squares discriminant analysis (OPLS-DA). Weighted gene coexpression network analysis (WGCNA) was performed to classify metabolites into modules for identifying biological pathways involved in hepatocarcinogenesis. We assessed the risk predictivity of metabolites using multivariable logistic regression models. Among 612 named metabolites, 44 differential metabolites were identified between cases and controls, including 12 androgenic/progestin steroid hormones, 8 bile acids, 10 amino acids, 6 phospholipids, and 8 others. These metabolites were associated with HCC in the multivariable logistic regression analyses, with odds ratios ranging from 0.19 (95% confidence interval [CI]: 0.11-0.35) to 5.09 (95% CI: 2.73-9.50). WGCNA including 612 metabolites showed 8 significant modules related to HCC risk, including those representing metabolic pathways of androgen and progestin, primary and secondary bile acids, and amino acids. A combination of 18 metabolites of independent effects showed the potential to predict HCC risk, with an AUC of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.93) in the training and validation sets, respectively. In conclusion, we identified a panel of plasma metabolites that could be implicated in hepatocellular carcinogenesis and have the potential to predict HCC risk.

Abstract Rationale The association between fine particulate matter (particulate matter ⩽2.5 μm in aerodynamic diameter, PM2.5) and lung cancer incidence in nonsmokers (LCINS) remains inconsistent. Objectives To investigate the association between long-term PM2.5 exposure and LCINS in a Chinese population and to assess the modifying effect of genetic factors. Methods Time-dependent Cox proportional hazard models were used to evaluate the hazard ratios (HRs) and 95% confidence intervals (CIs) of PM2.5 with LCINS risk and LCINS-related mortality. The polygenic risk score was constructed to further explore the interactions between genetic risk and PM2.5 exposure. In addition, the population attributable fraction of PM2.5 to lung cancer risk and mortality was calculated. Measurements and Main Results The results demonstrated significant associations between PM2.5 exposure and LCINS incidence (HR, 1.10 per 10 μg/m3; 95% CI, 1.04–1.17 per 10 μg/m3) and mortality (HR, 1.17 per 10 μg/m3; 95% CI, 1.08–1.27 per 10 μg/m3). Compared with the lowest-risk group, individuals exposed to the high PM2.5 concentration (⩾50.9 μg/m3) and high genetic risk (top 30%) exhibited the highest LCINS incidence (HR, 2.01; 95% CI, 1.39–2.87) and mortality (HR, 2.30; 95% CI, 1.38–3.82). A significant additive interaction between PM2.5 and genetic risk on LCINS incidence was observed. Approximately 33.6% of LCINS cases and 48.5% of LCINS-related deaths in China could be prevented if PM2.5 concentrations were reduced to meet World Health Organization guidelines. Conclusions Long-term exposure to outdoor PM2.5 increases LCINS risk and LCINS-related mortality, especially in populations with high genetic risk. Strengthening air pollution control measures in China has the potential to significantly reduce the burden of LCINS.

BACKGROUND: The fecal immunochemical test (FIT) has been widely used in colorectal cancer (CRC) screening, yet the practical performance of FIT combined with questionnaire-based risk assessment (QRA) remains undetermined. Moreover, risk factors for distinct CRC precursors identified in screening have been rarely compared. METHODS: This study was based on a population-based CRC screening in China, with 2,120,340 participants completing both FIT and QRA. Those with positive FIT or high QRA scores were recommended for colonoscopy. We reported the compliance, detection rate, and colonoscopy workload according to FIT and QRA results. We also explored risk factors for conventional adenomas and serrated polyps. RESULTS: The compliance rate of colonoscopy in the subgroup of FIT (+) and QRA (+) was 41.4%, higher than the rates in FIT (+) and QRA (-), as well as FIT (-) and QRA (+), which were 38.7% (P < 0.001) and 16.4% (P < 0.001), respectively. The corresponding detection rates of advanced neoplasia were 18.2%, 13.2%, and 9.3% (all P < 0.001), respectively. Moreover, the required numbers of colonoscopies to detect one advanced neoplasia in the three subgroups were 5.5, 7.6, and 10.8, respectively. Increased body mass index, smoking, alcohol consumption, red meat intake, and type 2 diabetes were associated with higher risk of advanced adenomas and advanced serrated polyps, whereas vegetable intake was inversely associated with advanced adenomas. CONCLUSION: FIT and QRA can synergistically identify individuals at high risk of colorectal advanced neoplasia, with those testing positive for both deserving immediate attention. Modifiable factors were identified to complement screening for preventing CRC precursors.