Recent trends in the incidence of early-onset prostate cancer.

Early-onset prostate cancer (EOPC) is relatively uncommon. It is unclear if the incidence of EOPC is evolving. Utilizing data from the SEER database from 2000 to 2020, the study identified prostate cancer cases in men under 55 years, focusing on trends in annual age-adjusted incidence rates (AAIR), stage at presentation, race/ethnicity, and local treatment patterns. The study encompassed 93 071 cases of EOPC, with the median age at diagnosis being 51 years. From 2000 to 2007, the AAIR of EOPC experienced a wave-like increase from 6.9 to 8.3 per 100 000 people. It then sharply declined to 5.4 by 2014, followed by 6 years of stability, and by 2020 it had dropped to its lowest point of 4.5. The trend observed across different racial groups was consistent with the overall pattern, where non-Hispanic Black patients consistently exhibited the highest incidence and the least reduction rate (annual percent change, -1.0; 95% confidence interval, -1.8 to -0.2; P < 0.05). Stage II was the most commonly diagnosed, although its AAIR declined from 4.9 to 1.2 per 100 000 people. From 2010 through 2020, the proportion of receiving prostatectomy decreased from 63.0 to 43.6%. The declining rates of EOPC across diverse racial groups emphasize the critical need for focused research and interventions. Specifically, there is an urgent call to establish a tailored screening protocol for prostate cancer targeting Black youth.

Apoptosis-Associated Gene Expression Profiling Is One New Prognosis Risk Predictor of Human Rectal Cancer.

Background: Prior research has revealed the predictive significance of a series of genetic markers in the prognosis of rectal cancer (RC), but the roles of apoptosis-associated genes in RC are rarely studied. Methods: The RNA-seq data as well as clinical data about patients with rectum adenocarcinoma (READ) were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project. Additionally, 87 apoptosis-associated genes were downloaded and acquired from Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Comprehensive bioinformatics analysis was carried out for deep exploration of the expression and prognostic significance of these genes. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis was performed for the establishment of a risk scoring equation for the prognosis model and construction of a survival prognosis model. ROC curves were drawn for evaluating the accuracy of the model. A real-time quantitative PCR assay was conducted for quantification of apoptosis-associated proteins related to prognosis. Results: Eight genes were identified as hub genes associated with the prognosis of PFS. A risk model of prognosis prediction based on four gene signatures (CYCS, IKBKB, NFKB1, and TRADD) was constructed. According to further analysis of this model, the high-risk group experienced worse overall survival than the other. The prognosis model demonstrated a favorable predictive ability, with areas under the receiver operating characteristic curves (AUC) of 0.720, 0.641, and 0.677 in forecasting the 1-, 2-, and 3-year prognosis, respectively. In addition, CYCS and NFKB1 presented low expression, while IKBKB and TRADD presented high expression in TCGA and clinical tumor samples. Conclusions: A four-gene signature risk model for prognosis forecasting of RC has been constructed, which possesses favorable predictive ability, which offers ideas and breakthrough points to the apoptosis-associated development of RC.