Dietary Factors and the Risk of Colorectal Cancer: A Mendelian Randomization Study.

OBJECTIVE: To examine the causal association between 15 dietary factors and the incidence of colorectal cancer through the application of Mendelian randomization methodology. METHODS: The data associated with 15 dietary factors were derived from the IEU OPEN GWAS database, and the colorectal cancer data were sourced from the FinnGen database. The Inverse Variance Weighting method was the principal research method. Sensitivity analyses were implemented to affirm the robustness of the findings. Additionally, we conducted multivariable Mendelian randomization analyses to adjust for the intake of ω-3 and ω-6 polyunsaturated fatty acids. RESULTS: In our research, we observed suggestive causal relationships between genetically predicted water intake and the reduced risk of colorectal cancer (OR = 0.54; 95% CI= 0.31 ∼ 0.93; p = 0.028); genetically predicted ω-3 PUFA intake (OR = 1.17; 95% CI= 1.05 ∼ 1.30; p = 0.005) were suggestively associated with the increased risk of colorectal cancer. In the multivariable Mendelian randomization analysis, the effect of ω-3 PUFA intake remains significant after adjusting for the influence of ω-6 PUFA intake. Horizontal pleiotropy was not present in this study. CONCLUSIONS: There exists a suggestive causal association between increased water intake and decreased risk of colorectal cancer, while ω-3 PUFA intake are suggestive linked to the increased risk of colorectal cancer.

Unhealthy lifestyle factors and the risk of colorectal cancer: a Mendelian randomization study.

The purpose of this study was to investigate the causal association between unhealthy lifestyle style factors and the risk of colorectal cancer, with the aim of preventing the occurrence of colorectal cancer by modifying unhealthy lifestyles. A two-sample Mendelian randomization (MR) approach was employed in this study, utilizing the inverse-variance weighted method as the primary research method. This MR analysis analyzed data of 3022 colorectal cancer cases and 174,006 controls from the FinnGen database. Single nucleotide polymorphisms (SNPs) associated with unhealthy lifestyle factors were selected as instrumental variables (IVs), including two obesity-related indicators, BMI (body mass index) and WHR (waist-to-hip ratio). Four phenotypes of smoking (smoking initiation, ever smoked, smoking per day, smoking cessation) and one phenotype of alcohol consumption (drinks per week). Four phenotypes of physical activity (accelerometer-based physical activity, moderate-to-vigorous physical activity, vigorous physical activity, strenuous sports or other exercises). All SNPs were obtained from published genome-wide association studies. The study found that the obesity-related indicator, higher WHR (OR = 1.38, 95% CI 1.12-1.70; P = 0.002) were associated with an increased risk of colorectal cancer, and two smoking phenotypes, cigarettes per day(OR = 1.30, 95% CI 1.01-1.68; P = 0.042)and smoking initiation (OR = 3.48, 95% CI 1.15-10.55; P = 0.028), were potentially associated with an increased risk of colorectal cancer. However, there was no evidence to suggest that physical activities and alcohol consumption were associated with colorectal cancer (all p > 0.05). In addition, the study detected no pleiotropy (all p > 0.05). This MR analysis indicates a causal association between a higher waist-to-hip ratio and the risk of colorectal cancer and a suggestive association between smoking and the risk of colorectal cancer among Europeans. These findings contribute to the understanding of the etiology of colorectal cancer and have potential implications for its prevention.

Integrating transcriptomics and machine learning for immunotherapy assessment in colorectal cancer.

Colorectal cancer (CRC) is a highly prevalent and lethal malignancy worldwide. Although immunotherapy has substantially improved CRC outcomes, intolerance remains a major concern among most patients. Considering the pivotal role of the tumor microenvironment (TME) in tumor progression and treatment outcomes, profiling the TME at the transcriptomic level can provide novel insights for developing CRC treatment strategies. Seventy-seven TME-associated signatures were acquired from previous studies. To elucidate variations in prognosis, clinical features, genomic alterations, and responses to immunotherapy in CRC, we employed a non-negative matrix factorization algorithm to categorize 2595 CRC samples of 27 microarrays from the Gene Expression Omnibus database. Three machine learning techniques were employed to identify a signature specific to immunotherapy. Subsequently, the mechanisms by which this signature interacts with TME subtypes and immunotherapy were investigated. Our findings revealed five distinct TME subtypes (TMESs; TMES1-TMES5) in CRC, each exhibiting a unique pattern of immunotherapy response. TMES1, TMES4, and TMES5 had relatively inferior outcomes, TMES2 was associated with the poorest prognosis, and TMES3 had a superior outcome. Subsequent investigations revealed that activated dendritic cells could enhance the immunotherapy response rate, with their augmentation effect closely associated with the activation of CD8+T cells. We successfully classified CRC into five TMESs, each demonstrating varying response rates to immunotherapy. Notably, the application of machine learning to identify activated dendritic cells helped elucidate the underlying mechanisms contributing to these differences. We posit that these TMESs hold promising clinical implications for prognostic evaluation and guidance of immunotherapy strategies, thereby providing valuable insights to inform clinical decision-making.

CircSTK3 drives the metastasis of colorectal cancer by regulating epithelial-mesenchymal transition.

Circular RNAs (circRNAs) play crucial roles in malignancies. We aimed to delineate the functions and clinical importance of dysregulated circRNAs in colorectal cancer (CRC). We determined the circRNA expression profile from five CRC and paired adjacent normal tissues using circRNA microarray. We found that a novel circRNA, hsa_circ_0004592 (named circSTK3), was significantly upregulated in CRC tissues and correlated with decreased survival. Loss- and gain-of-function assays revealed that circSTK3 promoted the migration and invasion but not proliferation of cells. Whole genome expression microarray identified potential downstream targets and the regulatory networks of circSTK3; Gene Ontology analysis confirmed circSTK3 involvement in the CRC metastasis phenotype. Abnormal circSTK3 expression affected a subset of genes associated with CRC metastasis and triggered epithelial-mesenchymal transition programming, maintaining a tumor-promoting signature. Moreover, circSTK3 was transcriptionally regulated by CTCF. These findings reveal the functional and prognostic roles of circSTK3 and expose circRNAs as key players in metastasis.

Nomogram to Predict the Risk of Postoperative Anxiety and Depression in Colorectal Cancer Patients.

Purpose: To develop and validate the risk nomogram to predict the likelihood of postoperative anxiety and depression in colorectal cancer (CRC) patients. Methods: A total of 602 CRC patients from the Second Affiliated Hospital of Harbin Medical University were included in the study and divided into development set and validation set with the 2:1 ratio randomly. Logistic regression model was used to determine independent factors contributing to postoperative anxiety and depression, which were subsequently applied to build the nomogram for predicting postoperative anxiety and depression. The performance of the risk nomogram was appraised by the area under the receiver operating curve (AUC), calibration curves and decision curve analyses (DCA). Results: Gender, personal status, income, adjuvant therapy, the Eastern Cooperative Oncology Group Scale (ECOG) score, comorbidity, postoperative complications and stoma status were significant indicators for postoperative anxiety and depression. The AUCs for the development and validation sets were 0.792 and 0.812 for the postoperative anxiety nomogram and 0.805 and 0.825 for the postoperative depression nomogram. Additionally, calibration curves and decision curve analyses also determined the reliable clinical importance of the proposed nomogram. Conclusion: The current study constructed the risk nomogram for postoperative anxiety and depression and could help clinicians determine high-risk patients to some extent.

Gut microbiota display alternative profiles in patients with early-onset colorectal cancer.

Background: The incidence of early-onset colorectal cancer (EOCRC) is increasing worldwide. This study aimed to explore whether there is an alternative gut microbiota profile in patients with early-onset colorectal cancer. Methods: A total of 24 patients with EOCRC, 43 patients with late-onset colorectal cancer and 31 young volunteers were included in this study. The diversity of their fecal bacteria was explored using 16S ribosomal RNA gene sequencing. Cluster of ortholog genes (COG) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) were used to detect enrichment pathways among the three groups. Results: Community separations were observed among the three groups. The Shannon index of the EOCRC group was significantly lower than the LOCRC group (P=0.007) and the NC group (P=0.008). Both PCoA analysis (Principal co-ordinates analysis, P=0.001) and NMDS (non-metric multidimensional scaling, stress=0.167, P=0.001) analysis indicated significant difference in beta diversity among the three groups. Fusobacteria, Bacteroidetes, and Clostridia were the most abundant bacteria in the EOCRC group, LOCRC group, and NC group, respectively. The results of COG showed that transcription (P=0.01398), defense mechanisms (P=0.04304), inorganic ion transport and metabolism (P=0.00225) and cell wall/membrane/envelope biogenesis (P=0.02534) were differentially expressed among the three groups. The KEGG modules involved in membrane transport (P=0.00856) and porphyrin and chlorophyll metabolism (P=0.04909) were differentially expressed among the three groups. Conclusion: Early-onset colorectal cancer patients have a different gastrointestinal microbiota derangement compared to late-onset colorectal cancer patients. This dysbiosis can be reflected in the species diversity of the microbiota, the abundance of bacteria, and the abnormal functional predictions.