Background:The cancer burden in the United States of America (USA) has decreased gradually. However, China is experiencing a transition in its cancer profiles, with greater incidence of cancers that were previously more common in the USA. This study compared the latest cancer profiles, trends, and determinants between China and USA.Methods:This was a comparative study using open-source data. Cancer cases and deaths in 2022 were calculated using cancer estimates from GLOBOCAN 2020 and population estimates from the United Nations. Trends in cancer incidence and mortality rates in the USA used data from the Surveillance, Epidemiology, and End Results program and National Center for Health Statistics. Chinese data were obtained from cancer registry reports. Data from the Global Burden of Disease 2019 and a decomposition method were used to express cancer deaths as the product of four determinant factors.Results:In 2022, there will be approximately 4,820,000 and 2,370,000 new cancer cases, and 3,210,000 and 640,000 cancer deaths in China and the USA, respectively. The most common cancers are lung cancer in China and breast cancer in the USA, and lung cancer is the leading cause of cancer death in both. Age-standardized incidence and mortality rates for lung cancer and colorectal cancer in the USA have decreased significantly recently, but rates of liver cancer have increased slightly. Rates of stomach, liver, and esophageal cancer decreased gradually in China, but rates have increased for colorectal cancer in the whole population, prostate cancer in men, and other seven cancer types in women. Increases in adult population size and population aging were major determinants for incremental cancer deaths, and case-fatality rates contributed to reduced cancer deaths in both countries.Conclusions:The decreasing cancer burden in liver, stomach, and esophagus, and increasing burden in lung, colorectum, breast, and prostate, mean that cancer profiles in China and the USA are converging. Population aging is a growing determinant of incremental cancer burden. Progress in cancer prevention and care in the USA, and measures to actively respond to population aging, may help China to reduce the cancer burden.

BACKGROUND: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (GÂG) interactions.RESEARCH QUESTION: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis? STUDY DESIGN AND METHODS: Biomarker screening and model validation were used to construct and validate a prognostic prediction model. NSCLC prognosis-associated biomarkers were identified on the basis of either their main effects or interactions with two types of omics data. A prognostic score incorporating epigenetic and transcriptional biomarkers, as well as clinical information, was independently validated.RESULTS: Twenty-six pairs of biomarkers with GÂG interactions and two biomarkers with main effects were significantly associated with NSCLC survival. Compared with a model using clinical information only, the accuracy of the epigenetic and transcriptional biomarker-based prognostic model, measured by area under the receiver operating characteristic curve (AUC), increased by 35.38% (95% CI, 27.09%-42.17%; P ¼ 5.10 Â 10 -17 ) and 34.85% (95% CI, 26.33%-41.87%; P ¼ 2.52 Â 10 -18 ) for 3-and 5-year survival, respectively, which exhibited a superior predictive ability for NSCLC survival (AUC 3 year , 0.88 [95% CI, 0.83-0.93]; and AUC 5 year , 0.89 [95% CI, 0.83-0.93]) in an independent Cancer Genome Atlas population. GÂG interactions contributed a 65.2% and 91.3% increase in prediction accuracy for 3-and 5-year survival, respectively. INTERPRETATION:The integration of epigenetic and transcriptional biomarkers with main effects and GÂG interactions significantly improves the accuracy of prognostic prediction of early-stage NSCLC survival.