Cancer is a leading cause of death worldwide, posing a huge burden upon society and individuals. The adequate intake of fruit and vegetables is reported to be an effective strategy for primary cancer prevention. Fruits and vegetables are rich in nutrients, such as vitamins and flavonoids, which may reduce the occurrence and progression of cancers. However, the importance of each flavonoid and the sub-classes remains controversial regarding cancer mortality. The population benefiting from increased flavonoid intake has not been determined. An estimation of cancer mortality by flavonoid intake is not established. We explored the association between the intake of flavonoids and cancer mortality amongst 14,029 participants in the National Health and Nutrition Examination Survey. During a median follow-up of 117 months, 405 cancer deaths were confirmed. Being in the second, third, and fourth quartiles of flavonol intake, the cancer mortality was inversely associated with the intake of flavonols (multivariate analysis HR (95% CI] 0.58 [0.36, 0.91], p = 0.02, Q1 vs. Q2; 0.55 [0.31, 0.96], p = 0.04, Q1 vs. Q3; 0.54 [0.30, 0.99], p = 0.05, Q1 vs. Q4, respectively). Potential effects of dietary flavonol intake against cancer death was observed especially in participants aged 50 or above, males, whites, former smokers, people who used to drink or drink alcohol mildly, people without hyperlipidemia, and people with hypertension. Moreover, the dietary intakes of peonidin, naringenin, and catechin were inversely associated with cancer mortality (multivariate HR [95% CI] 0.93 [0.88,0.98], p = 0.01; 0.97 (0.95,1.00), p = 0.03; 0.98 (0.96,1.00), p = 0.05, respectively). Furthermore, a nomogram based on flavonol intake is feasible for assessing cancer mortality for each participant. Taken together, our results could improve personalized nutrition amongst cancer patients.

Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron‐dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis‐related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune‐associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA‐ESCC database were designated as the training cohort. A ten‐FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real‐time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten‐FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high‐risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low‐risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

Objective: We used bioinformatics analysis to identify potential biomarker genes and their relationship with breast cancer (BC). Materials and Methods: We used a weighted gene co-expression network analysis (WGCNA) to create a co-expression network based on the top 25% genes in the GSE24124, GSE33926, and GSE86166 datasets obtained from the Gene Expression Omnibus. We used the DAVID online platform to perform GO and KEGG pathway enrichment analyses and the Cytoscape CytoHubba plug-in to screen the potential genes. Then, we related the genes to prognostic values in BC using the Oncomine, GEPIA, and Kaplan–Meier Plotter databases. Findings were validated by immunohistochemical (IHC) staining in the Human Protein Atlas and the TCGA-BRCA cohort. LinkedOmics identified the interactive expressions of hub genes. We used UALCAN to evaluate the methylation levels of these hub genes. MethSurv and SurvivalMeth were used to assess the multilevel prognostic value. Finally, we assessed hub gene association with immune cell infiltration using TIMER. Results: The mRNA levels of MKI67, UBE2C, GTSE1, CCNA2, and MND1 were significantly upregulated in BC, whereas ESR1, THSD4, TFF1, AGR2, and FOXA1 were significantly downregulated. The DNA methylation signature analysis showed a better prognosis in the low-risk group. Further subgroup analyses revealed that MND1 might serve as an independent risk factor for unfavorable BC prognosis. Additionally, MND1 expression levels positively correlate with the immune infiltration statuses of CD4+ T cells, CD8+ T cells, B cells, neutrophils, dendritic cells, and macrophages. Conclusion: Our results indicate that the ten hub genes may be involved in BC’s carcinogenesis, development, or metastasis, and MND1 may be a potential biomarker and therapeutic target for BC.

Adequate intake of flavonoids may influence mortality, particularly of heart and cerebrovascular diseases. However, the importance of each flavonoid and its subclasses in preventing all-cause and disease-specific mortalities remain unclear. In addition, it is unknown which population groups would benefit from high flavonoid intake. Therefore, personalized mortality risk based on flavonoid intake needs to be estimated. The association between flavonoid intake and mortality among 14,029 participants in the National Health and Nutrition Examination Survey was examined using Cox proportional hazards analysis. A prognostic risk score and nomogram linking flavonoid intake and mortality were constructed. During a median follow-up of 117 months (9.75 years), 1,603 incident deaths were confirmed. Total flavonol intake was associated with a significantly reduced all-cause mortality [multivariable adjusted hazard ratio [HR] (95% confidence interval [CI]), 0.87 (0.81, 0.94), p for trend <0.001], especially in participants aged 50 years and older and former smokers. Similarly, total anthocyanidin intake was inversely associated with all-cause mortality [0.91 (0.84, 0.99), p for trend = 0.03], which was most significant in non-alcoholics. The intake of isoflavones was negatively associated with all-cause mortality [0.81 (0.70, 0.94), p = 0.01]. Moreover, a risk score was constructed based on survival-related flavonoid intake. The constructed nomogram accurately predicted the all-cause mortality of individuals based on flavonoid intake. Taken together, our results can be used to improve personalized nutrition.

This study aimed to investigate the prognostic value of the Naples Prognostic Score (NPS) in patients with locally advanced cervical cancer (LACC) who received curative concurrent chemoradiotherapy (CCRT). Clinicopathological data from 213 (training set) and 106 (validation set) LACC cases undergoing CCRT were retrospectively analyzed. The receiver operating characteristic curve (ROC) was used to compare the predictive ability of NPS and other indicators for survival. Cox proportional hazard regression was conducted for overall survival (OS) and progression-free survival (PFS). A prediction model using a nomogram was developed with independent prognostic factors in the training set and validated in the validation set. The 5-year OS for the NPS = 1, 2, and 3 groups was 56.8%, 45.4%, and 28.9% (P < 0.001), and the 5-year PFS for the NPS = 1, 2, and 3 groups was 44.9%, 36.7%, and 28.4% (P = 0.001), respectively. NPS showed better predictive ability for OS and PFS compared to other indicators. Multivariate regression analysis identified NPS as an independent prognostic factor for OS (P < 0.001) and PFS (P < 0.001). A predictive nomogram based on NPS was established and validated. The C-indices of the nomogram in the training set were 0.722 for OS and 0.683 for PFS, while in the validation set the C-indices were 0.731 for OS and 0.693 for PFS. This study confirmed that preoperative NPS could serve as a useful independent prognostic factor in LACC patients treated with CCRT.