Recent studies have demonstrated the biological significance of cuproptosis modification, a newly discovered programmed cell death, in tumor progression. Nonetheless, the potential role of cuproptosis-related genes (CRGs) in the immune landscape and tumor microenvironment (TME) formation of colorectal cancer (CRC) remains unknown. We comprehensively assessed cuproptosis modification patterns of 1339 CRC samples based on 27 CRGs and systematically analyzed the correlation of these patterns with TME. The CRG-score was constructed to quantify cuproptosis characteristics by LASSO and multivariate Cox regression methods, and its predictive capability was validated in an independent cohort. We identified three distinct cuproptosis modification patterns in CRC. The TME immune cell infiltration demonstrated immune heterogeneity among these three subtypes. Enrichment for multiple metabolism signatures was pronounced in cluster A. Cluster C was significantly correlated with the signaling pathways of immune activation-related, resulting in poor prognoses. Cluster B with mixed features possibly represents a transition phenotype or intratumoral heterogeneity. Then, based on constructed eight-gene CRG-score, we found that the signature could predict the disease-free survival of CRC patients, and the low CRG-score was related to increased neoantigen load, immunity activation, and microsatellite instability-high (MSI-H). Additionally, we observed significant correlations of the CRG-score with the cancer stem cell index and chemotherapeutic drug susceptibility. This study demonstrated that cuproptosis was correlated with tumor progression, prognosis, and TME. Our findings may improve the understanding of CRGs in TME infiltration characterization of CRC patients and contribute to guiding more effective clinical therapeutic strategies.
BackgroundImmune checkpoint inhibitor (ICI) therapy has proven to be a promising treatment for colorectal cancer (CRC). We aim to investigate the relationship between DNA methylation and tumor mutation burden (TMB) by integrating genomic and epigenetic profiles to precisely identify clinical benefit populations and to evaluate the effect of ICI therapy.MethodsA total of 536 CRC tissues from the Cancer Genome Atlas (TCGA) with mutation data were collected and subjected to calculate TMB. 80 CRC patients with high TMB and paired normal tissues were selected as training sets and developed the diagnostic and prognostic methylation models, respectively. In the validation set, the diagnostic model was validated in our in-house 47 CRC tissues and 122 CRC tissues from the Gene Expression Omnibus (GEO) datasets, respectively. And a total of 38 CRC tissues with high TMB from the COLONOMICS dataset verified the prognostic model.ResultsA positive correlation between differential methylation positions and TMB level was observed in TCGA CRC cohort (r=0.45). The diagnostic score that consisted of methylation levels of four genes (ADHFE1, DOK6, GPR75, and MAP3K14-AS1) showed high diagnostic performance in the discovery (AUC=1.000) and two independent validation (AUC=0.946, AUC=0.857) datasets. Additionally, these four genes showed significant positive correlations with NK cells. The prognostic score containing three genes (POU3F3, SYN2, and TMEM178A) had significantly poorer survival in the high-risk TMB samples than those in the low-risk TMB samples (P=0.016). CRC patients with low-risk scores combined with TMB levels represent a favorable survival.ConclusionsBy integrating analyses of methylation and mutation data, it is suggested that DNA methylation patterns combined with TMB serve as a novel potential biomarker for early screening in more high-TMB populations and for evaluating the prognostic effect of CRC patients with ICI therapy.
Objectives: Sedentary behavior (SB) and physical inactivity have been associated with an increased risk of all-cause mortality. Evidence in China is scarce, and it is unclear whether physical activity (PA) attenuates or even eliminates the harmful effects of prolonged SB in the Chinese population. Methods:We conducted a prospective cohort study of 17 084 Chinese adults.PA and sitting time (ST) were assessed using the IPAQ. Cox proportional hazards models were used to estimate the risk of PA and ST with all-cause mortality.Interaction plots were used to visualize the interaction effects.Results: During a median follow-up of 6.01 years, a total of 1106 deaths occurred.PA level was inversely associated with the incidence of all-cause mortality, while ST showed a detrimental association (all p trend < 0.05). In the stratified analysis, ST was associated with all-cause mortality in the low PA, while the association was attenuated in the moderate PA group: the HRs (95% CI) comparing ST of 4-8, 8-11, and ≥11 to <4 h/day were 1.15 (0.73-1.81), 1.55 (0.92-2.59), and 2.70 (1.52-4.80), respectively. In the high PA group, no significant association was found across all ST levels. In the joint analysis, compared with the high PA and ST <4 h/ day, the harmful effect was found only in the combined low PA and moderate PA groups with ST ≥11 h/day (HR:2.71, 95% CI:1.69-4.35). In addition, a significant interaction association was found. Conclusion:Our study, based on a prospective cohort, suggests that the detrimental effect of ST on all-cause mortality is attenuated or eliminated by high PA levels in the Chinese population.
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