Colorectal carcinoma (CRC) is a leading cause of cancer-related deaths globally. Diagnostic biomarkers are essential for risk stratification and early detection, potentially enhancing patient survival. Our study aimed to explore the potential biomarkers of CRC at the protein and metabolic levels.

Blood serum from CRC patients and healthy controls was analyzed using metabolomic and proteomic techniques. A conjoint analysis was conducted, and samples were split into training and validation sets (7:3 ratio) to develop and evaluate a disease diagnosis classifier model. Immunohistochemistry (IHC) analyses were conducted to validate the results.

We identified 631 differential metabolites and 61 differentially expressed proteins (DEPs) in CRC, involved in pathways such as arginine and proline metabolism, central carbon metabolism in cancer, and signaling pathways including TGF-β, mTOR, PI3K-Akt, and others. Key proteins (CILP2, SLC3A2, EXTL2, hydroxypyruvate isomerase (HYI), ENPEP, LRG1, CTSS, thyrotropin-releasing hormone-degrading ectoenzyme (TRHDE), SELE, and HSPA1A) showed significant expression differences between CRC patients and controls. IHC results showed that compared with the paracancerous tissues, the expression of CILP2, EXTL2, and HYI was significantly downregulated in the CRC tissues (P < 0.05). The classifier model, comprising l-arginine, Harden-Young ester, l-aspartic acid, oxoglutaric acid, l-proline, octopine, l-valine, and progesterone, achieved AUC values of 0.998 and 0.914 in training and validation data sets, respectively.

The identified metabolites and DEPs are promising CRC biomarkers. The developed classifier model based on eight metabolites demonstrates high accuracy for CRC assessment and diagnosis.

The study aimed to quantitatively detect the suppressors of cytokine signaling (SOCS) 3 promoter methylation levels, investigate the relationship between SOCS3 methylation and gene expression, and construct a prognosis prediction model combined with clinical indicators for Acute-on-chronic Hepatitis B Liver Failure (ACHBLF).

A total of 135 ACHBLF patients were enrolled and randomly divided into the training cohort and validation cohort. The SOCS3 mRNA and promoter methylation in peripheral blood mononuclear cells (PBMCs) of ACHBLF patients were quantitative measured. A clinical prediction model was established based on SOCS3 promoter methylation and clinical indicators. The prediction model was evaluated by the area under the receiver operating characteristic curve, the Hosmer-Lemeshow (H-L) goodness-of-fit test, and decision curve analysis.

In this study, compared with ACHBLF survivals, SOCS3 showed lower mRNA levels and higher methylation levels in ACHBLF non-survivals. The SOCS3 methylation rates were negatively correlated with SOCS3 mRNA levels. PT-INR, IL-6, and percentage of the methylation reference (PMR) value (SOCS3) were used to establish a clinical model for predicting ACHBLF patients' prognosis. The results of AUC, the Hosmer-Lemeshow (H-L) goodness-of-fit test and decision curve analysis (DCA) showed that the prediction model had good clinical applicability. The prediction model was visualized.

A prognosis prediction model for ACHBLF was developed based on PMR (SOCS3), PT-INR and IL-6, which may have a good potential clinical application value.

Clear cell renal cell carcinoma (ccRCC), a predominant subtype of renal cell carcinoma, significantly contributes to the heightened morbidity and mortality in individuals diagnosed with urologic tumors. The challenges posed by high malignancy at the initial diagnosis of ccRCC, therapeutic resistance, and unfavorable patient prognosis remain largely unresolved. Our findings indicate that SEPT5 is upregulated in ccRCC and this upregulation is associated with an adverse prognosis for ccRCC patients. Furthermore, we demonstrate that overexpression of SEPT5 promotes proliferation of ccRCC cells, alters their cell cycle distribution, and enhances their migratory and invasive capabilities. Additionally, we observe a positive correlation between SEPT5 overexpression and resistance to sorafenib and sunitinib in ccRCC cells. Further mechanistic investigations have revealed that SEPT5 serves as a novel direct transcriptional target of HIF-1α, leading to subsequent reduction in protein expression and nuclear translocation of HIF-1α. This establishes a feedback loop in ccRCC tumorigenesis. Ultimately, knockdown of SEPT5 significantly inhibits xenografted tumor growth in vivo. Overall, this study provides compelling evidence that directly targeting the HIF-1α-SEPT5 feedback axis may be an effective approach for suppressing the proliferation and progression of ccRCC, offering new insights into the diagnosis and treatment of ccRCC patients.

Colorectal cancer (CRC) is a significant worldwide health problem due to its high prevalence, mortality rates, and frequent diagnosis at advanced stages. While diagnostic and therapeutic approaches have evolved, the underlying mechanisms driving CRC initiation and progression are not yet fully understood. Early detection is critical for improving patient survival, as initial cancer stages often exhibit epigenetic changes-such as DNA methylation-that regulate gene expression and tumor progression. Identifying DNA methylation patterns and key survival-related genes in CRC could thus enhance diagnostic accuracy and extend patient lifespans. In this study, we apply two of our recently developed methods for identifying differential methylation and analyzing survival using a sparse, finite mixture of accelerated failure time regression models, focusing on key genes and pathways in CRC datasets. Our approach outperforms two other leading methods, yielding robust findings and identifying novel differentially methylated cytosines. We found that CRC patient survival time follows a two-component mixture regression model, where genes CDH11, EPB41L3, and DOCK2 are active in the more aggressive form of CRC, whereas TMEM215, PPP1R14A, GPR158, and NAPSB are active in the less aggressive form.

Primary live cancer (PLC), including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). This meta-analysis was conducted to evaluate the diagnostic efficacy of blood methylated septin 9 gene (mSEPT9) for PLC and to analyze its performance across various subgroups.

We conducted a comprehensive search across PubMed, the Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI), covering research up to May 10, 2024. The pooled sensitivity, specificity, diagnostic odds ratios, and area under the summary receiver operating characteristic (AUC) were calculated for the diagnostic performance of mSEPT9 for PLC. The quality of the studies was assessed using the QUADAS-2 tool, and the meta-analysis was performed using Stata16.0 software.

Ten articles with 2,182 participants were included in the meta-analysis. The pooled sensitivity of mSEPT9 for detecting primary liver cancer was 0.51 (95% confidence interval [CI]: 0.37-0.65), and the pooled specificity was 0.93 (95% CI: 0.78-0.98). The pooled diagnostic odds ratio was 13 (95% CI: -58), and the area under the Summary Receiver Operator Characteristic Curve was 0.75 (95% CI: 0.71-0.79). Subgroup analyses showed that ICC, case-control studies, qPCR and Asian populations had higher specificities (0.99 [95% CI: 0.97-1.00], 0.93 [95% CI: 0.91-0.95], 0.90 [95% CI: 0.88-0.92] and 0.94 [95% CI: 0.92-0.96], respectively) and diagnostic odds ratios (62.04 [95% CI: 6.53-589.53], 17.62 [95% CI: 4.03-76.99], 13.03 [95% CI: 2.01-84.63] and 14.19 [95% CI: 2.42-83.11], respectively) compared to hepatocellular carcinoma, cohort Study, and Euramerican populations.

This study confirmed that mSEPT9 in blood has high specificity and moderate sensitivity for detecting primary liver cancer. The diagnostic performance of mSEPT9 varied across different subgroups, limiting its use as an independent screening tool and necessitating its use in conjunction with other methods for confirmatory diagnostics.

https://www.crd.york.ac.uk/prospero/, identifier CRD42024549669.

Spatial patterns of cells and other biological elements drive physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple elements in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex spatial data. SPACE is compatible with any data collection modality that records values (i.e., categorical cell/structure types or quantitative expression levels) at fixed spatial coordinates (i.e., 2d pixels or 3d voxels). SPACE detects not only broad patterns of co-occurrence but also context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles of tissue elements-single elements, pairs, triplets, and so on-and ranks the most strongly patterned ensembles. For single images, rankings reflect differences from random assortment. For sets of images, rankings reflect differences across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then characterize the nature of each pattern for intuitive interpretation. We validate SPACE and demonstrate its advantages using murine lymph node images for which ground truth has been defined. We then detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

DNA hypomethylation and uracil misincorporation into DNA, both of which have a very important correlation with colorectal carcinogenesis. Folate plays a crucial role in DNA synthesis, acting as a coenzyme in one-carbon metabolism, which involves the synthesis of purines, pyrimidines, and methyl groups. MTHFR, a key enzyme in folate metabolism, has been widely studied in relation to neural tube defects and hypertension, but its role in colorectal cancer remains underexplored. Therefore, understanding the role of folate and MTHFR genes in colorectal cancer may be helpful for potential preventive or therapeutic interventions. In this meta-analysis, the effects of MTHFR genotype and folate intake on colorectal cancer incidence were analyzed.

We searched PubMed,Embase, Web of Science, and CNKI database to identify relevant studies up to January 2024. We included a series of studies on the association of MTHFR C677T genotype and folate intake with colorectal cancer incidence. The meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). It included 100 studies (39702 cases and 55718 controls),that investigated the association between the MTHFR C677T polymorphism and colorectal cancer (CRC). Additionally, the analysis incorporated further stratification by ethnic population and geographical region. Furthermore, Six of the studies which clarified high amount of folate might be a protective factor for CRC in all three MTHFR C677T genotype, especially in TT genotype.

MTHFR 677TT genotype was negatively associated with CRC incidence compared with CC genotype (OR = 0.89; 95% CI: 0.85-0.93; P < 0.00001; Z = 5.17). MTHFR 677CT genotype was not significantly associated with colorectal cancer incidence (OR = 1.00; 95% CI: 0.98,1.03). A negative correlation between TT genotype and CRC was observed in ethnics of Asians (OR = 0.83, 95% CI: 0.76, 0.91), Caucasians (OR = 0.93, 95% CI: 0.88, 0.99) and the region of USA (OR = 0.77, 95% CI: 0.71, 0.85), Asia (OR = 0.93, 95% CI: 0.86, 1.00) and Europe (OR = 0.93, 95% CI:0.87, 1.00),but not in Indian (TT: OR = 1.67, 95% CI: 1.06, 2.63; CT: OR = 1.31, 95% CI: 1.00, 1.73)). Amount folate intakes might reduce the morbidity of CRC for people in MTHFR 677TT genotype (OR = 0.68; 95% CI: 0.48,0.96; P = 0.03).

The analysis showed that the incidence of colorectal cancer was reduced among individuals with TT genotype. The individuals with TT genotype and amount folate intake may collectively improve the incidence of colorectal cancer. While the MTHFR 677TT genotype is associated with a reduced risk of CRC, especially in certain populations, these findings should be interpreted with caution due to the limitations of retrospective studies.

Genome-wide methylation studies have significantly advanced our understanding of colorectal adenocarcinoma progression and biomarker discovery. Aberrant DNA methylation plays a crucial role in gene expression regulation during cancer transformation, highlighting the need to identify differentially methylated regions (DMRs) as potential diagnostic and therapeutic markers. However, an integrated resource to explore and validate methylation alterations across colorectal cancer stages has been lacking. We aimed to develop a platform that integrates existing methylation data, systematically identifies DMRs and provides a tool for further investigation.

We created a database combining Illumina HumanMethylation450K and EPIC data from normal colon, adenoma and adenocarcinoma tissues, comprising 2346 samples from 19 datasets. Methylation levels were analysed in six gene regions, and comparisons between tissue types were made using Mann-Whitney, Kruskal-Wallis and ROC tests.

Both adenoma and adenocarcinoma samples exhibited a general decrease in methylation compared to healthy tissue. Differential methylation in genes such as ITGA4, NPY, IGFL1 and LRRC4 was validated. The strongest DMRs were observed in the C1orf70 gene's 5'UTR and TSS200 regions, with AUC values of 0.98 in both of the HM450K and EPIC datasets. We established an interactive web-based platform accessible at https://epigenplot.com/ enabling future analysis of individual gene regions.

Our study provides an integrated database of DNA methylation profiles across normal, adenoma and adenocarcinoma tissues, offering a valuable resource for biomarker discovery. The integrated web platform can serve as a tool for the development of methylation-based therapies in the future.

Globally, breast cancer is the most frequent type of cancer, and its early diagnosis and screening can significantly improve the probability of survival and quality of life of those affected. Liquid biopsy-based targets such as circulating tumor cells, circulating tumor DNA, and exosomes have been instrumental in the early discovery of cancer, and have been found to be effective in stage therapy, recurrence monitoring, and drug selection. Biosensors based on these target related biomarkers convert the tested substances into quantifiable signals such as electrical and optical signals through signal transduction, which has the advantages of high sensitivity, simple operation, and low invasiveness. This review provides an overview of the latest progress of liquid biopsy biomarkers in the diagnosis, prognosis and treatment of breast cancer, compares the application and advantages of different biosensors based on these biomarkers in the diagnosis of breast cancer, and analyzes the limitations and solutions of biosensor based methods.

Mono-ubiquitination of lysine 18 on histone H3 (H3K18ub), catalyzed by UHRF1, is a DNMT1 docking site that facilitates replication-coupled DNA methylation maintenance. Its functions beyond this are unknown. Here, we genomically map simultaneous increases in UHRF1-dependent H3K18ub and SUV39H1/H2-dependent H3K9me3 following DNMT1 inhibition. Mechanistically, transient accumulation of hemi-methylated DNA at CpG islands facilitates UHRF1 recruitment and E3 ligase activity toward H3K18. Notably, H3K18ub enhances SUV39H1/H2 methyltransferase activity and, in colon cancer cells, nucleates new H3K9me3 domains at CpG island promoters of DNA methylation-silenced tumor suppressor genes (TSGs). Disrupting UHRF1 enzyme activity prevents H3K9me3 accumulation while promoting PRC2-dependent H3K27me3 as a tertiary layer of gene repression in these regions. By contrast, disrupting H3K18ub-dependent SUV39H1/H2 activity enhances the transcriptional activating and antiproliferative effects of DNMT1 inhibition. Collectively, these findings reveal roles for UHRF1 and H3K18ub in regulating a hierarchy of repressive histone methylation signaling and rationalize a combination strategy for epigenetic cancer therapy.

The aging process will lead to a gradual functional decline in the human body, and even accelerate a significantly increased risk of degenerative diseases. DNA methylation patterns change markedly with one's age, serving as a biomarker of biological age and closely linked to the occurrence and progression of age-related diseases. Currently, diagnostic methods for individual degenerative diseases are relatively mature. However, aging often accompanies the onset of multiple degenerative diseases, presenting certain limitations in existing diagnostic models. Additionally, some identified DNA methylation biomarkers are typically applicable to only one or a few types of cancer or diseases, further restricting their utility. We endeavor to screen for biomarkers associated with multiple degenerative diseases from the perspective of aging-related co-morbid mechanisms and to perform multiple degenerative disease diagnoses. In this study, we explored research based on methylation correlations and patterns to investigate shared mechanisms across multiple degenerative diseases, identifying a set of biomarkers associated with them. We validated these biomarkers with biological omics analysis and the prediction of multiple classes of degenerative diseases, screened the biomarkers from 600 to 110 by biological omics analysis, and demonstrated the validity and predictive ability of the screened 110 biomarkers. We propose a disease diagnostic model based on a multi-scale one-dimensional convolutional neural network (MSDCNN) and a multi-class degenerative disease prediction model (ResDegNet). The two models are well trained and tested to accurately diagnose diseases and categorize four types of degenerative diseases. The research identified 110 biomarkers associated with degenerative diseases, providing a foundation for further exploration of age-related degenerative conditions. This work aims to facilitate early diagnosis, the identification of biomarkers, and the development of therapeutic targets for drug interventions.

Colorectal cancer (CRC) is a major public health concern and the second leading cause of cancer-related deaths worldwide. However, challenges remain in deploying effective screening strategies for early-stage CRC. This study aimed to evaluate the effectiveness of a fecal-based syndecan-2 (SDC2) methylation test for the detection of colorectal lesions and CRC.

We retrospectively collected data on participants who underwent fecal SDC2 methylation testing from January 1, 2019, to May 30, 2023. Patients with positive results were recommended to undergo colonoscopy. Performance indicators associated with certain clinical characteristics, including positive rate (PR), positive predictive value (PPV), and colonoscopy compliance rate (CCR), were subjected to statistical analysis.

We analyzed data from 113,209 participants, of whom 11,841 (10.4% PR) had positive fecal SDC2 methylation test results. A total of 4315 participants with positive results adhered to the colonoscopy recommendations, and the CCR was 36.4%. Finally, 3169 colorectal lesions were detected, including 1134 polyps, 875 non-advanced adenomas (NAAs), 770 advanced adenomas (AAs), and 390 CRCs, with PPV values of 26.3% (1134/4315), 20.3% (875/4315), 17.8% (770/4315), and 9.0% (390/4315), respectively. Notably, the PPV for CRC increased significantly with age (χ 2 = 164.40, P < 0.0001). In addition, as the cycle threshold (CT) values increased, the PPVs of AAs and CRCs generally decreased, whereas those of NAAs and polyps significantly increased. Moreover, the clinical patient group had the highest incidence of late-stage CRC (stage II and higher), whereas asymptomatic populations from the staff physical examination group and rural town-based screening programs had the highest number of stage 0 and I CRCs detected (P = 0.0107).

This study indicates that fecal SDC2 methylation testing combined with colonoscopy may be an effective screening method for colorectal lesions and CRC.

Identifying differentially methylated regions (DMRs) is a basic task in DNA methylation analysis. However, due to the different strategies adopted, different DMR sets will be predicted on the same dataset, which poses a challenge in selecting a reliable and comprehensive DMR set for downstream analysis.

Here, we develop DMRIntTk, a toolkit for integrating DMR sets predicted by different methods on a same dataset. In DMRIntTk, the genome is segmented into bins, and the reliability of each DMR set at different methylation thresholds is evaluated. Then, the bins are weighted based on the covered DMR sets and integrated into final DMRs using a density peak clustering algorithm. To demonstrate the practicality of DMRIntTk, it was applied to different scenarios, including tissues with relatively large methylation differences, cancer tissues versus normal tissues with medium methylation differences, and disease tissues versus normal tissues with subtle methylation differences. Our results show that DMRIntTk can effectively trim regions with small methylation differences from the original DMR sets and thereby enriching the proportion of DMRs with larger methylation differences. In addition, the overlap analysis suggests that the integrated DMR sets are quite comprehensive, and functional analyses indicate the integrated disease-related DMRs are significantly enriched in biological pathways associated with the pathological mechanisms of the diseases. A comparative analysis of the integrated DMR set versus each original DMR set further highlights the superiority of DMRIntTk, demonstrating the unique biological insights it can provide.

Conclusively, DMRIntTk can help researchers obtain a reliable and comprehensive DMR set from many prediction methods.

Diffuse large B-cell lymphoma (DLBCL), known as the predominant type of aggressive B-cell lymphoma, is biologically and clinically heterogeneous. The prognosis of DLBCL is quite different among subtypes. Hypoxia is one of the key elements in tumor microenvironment, promoting tumor progression by means of various mechanisms, such as increased proliferation, altered metabolism, enhanced angiogenesis, and greater migratory capability, among others. The primary purpose of this research is to investigate the connection between hypoxia-featured genes (HFGs), prognosis in DLBCL, and their capacity association with the immune microenvironment. Various hypoxia-associated patterns for DLBCL patients from GEO and TCGA databases were identified by means of an unsupervised consensus clustering algorithm. CIBERSORT and IOBR package is used to identify different immune infiltration status. To develop a predictive model using hypoxia-related genes, we conducted univariate Cox regression, multivariate Cox regression, and LASSO regression assessment. Subsequently, we confirmed the predictive importance of these hypoxia-associated genes, highlighting hypoxia-associated characteristics, and explored the connection between the hypoxia model and the immune environment. Three hypoxia clusters were identified. We also observed that each pattern of hypoxia response was significantly related to different prognoses. It was found that the immune status among hypoxia clusters is different. After developing a prognostic risk model using 5 hypoxia-related genes, we discovered that the risk score is related to immune factors and how effective drugs are in treating DLBCL. In DLBCL patients, varying hypoxia patterns correlate with both prognostic outcomes and the immune microenvironment. Hypoxia-featured genes (HFGs) function as a standalone predictive element in these patients. It is also potentially a reliable indicator for predicting clinical responses to ICI therapy and traditional drugs.

This meta-analysis aimed to evaluate the prognostic significance of circulating long non-coding RNAs (lncRNAs) in colorectal cancer (CRC).

A comprehensive literature search was conducted in databases (Embase, Web of Science, PubMed, and Cochrane Library) up to July 2022. The quality of included studies was assessed using the Newcastle-Ottawa Scale (NOS). Statistical analysis was performed with Review Manager 5.4 and Stata 17.0. Publication bias was assessed using Begg's test, and sensitivity analysis was conducted to validate the meta-analysis results.

Ten articles, comprising 1,473 CRC patients and 18 different circulating lncRNAs, were included. Thirteen circulating lncRNAs were found to be up-regulated in CRC patients, while five were down-regulated. High expression of circulating lncRNAs up-regulated in CRC patients was associated with shorter CRC OS (HR = 2.91, 95% CI: 1.17, 7.22; P = 0.02, I2 = 86%). Conversely, high expression of circulating lncRNAs down-regulated in CRC patients was linked to longer CRC OS (HR = 0.16, 95% CI: 0.07, 0.40; P < 0.0001, I2 = 0%) and improved DFS (HR = 0.52, 95% CI: 0.37, 0.74; P = 0.0002, I2 = 0%). Additionally, circulating lncRNA levels correlated with TNM staging, tumor location, and lymph node metastasis.

Circulating lncRNAs show promise as prognostic markers for CRC patients, but further studies are warranted to validate these findings.

Colorectal cancer (CRC) is a prevalent malignancy with a high mortality rate, primarily due to liver metastasis. This study explores the role of centromere protein N (CENP-N) in mediating the methylation of septin 9 (SEPT9) and its subsequent effects on aerobic glycolysis and liver metastasis in CRC. We employed in vitro and in vivo experiments, including single-cell RNA sequencing, methylation-specific PCR (MSP), ChIP assays, and various functional assays to assess the impact of CENP-N and SEPT9 on CRC cell proliferation, migration, invasion, and metabolic reprogramming. Our data reveal that CENP-N directly interacts with SEPT9, enhancing its methylation at specific lysine residues. This modification significantly upregulates key glycolytic enzymes, thereby promoting aerobic glycolysis, CRC cell proliferation, and migration. In vivo studies further demonstrate that the CENP-N/SEPT9 axis facilitates liver metastasis of CRC, as confirmed by fluorescence imaging and histological analysis. This study identifies a novel pathway where CENP-N-mediated methylation of SEPT9 drives metabolic reprogramming and metastasis in CRC. These findings suggest potential therapeutic targets for inhibiting CRC progression and liver metastasis, offering new insights into CRC pathogenesis.

Several blood proteins might be associated with the development of colorectal cancer (CRC), but many studies on this topic are often biased. By using genetic variation data, which is less influenced by environmental factors, we can better determine the causal relationship between specific blood proteins and the occurrence of colorectal cancer.

Data from a genome-wide association study (GWAS) on blood proteins, encompassing 1,478 proteins, and colorectal cancer (CRC) GWAS data, covering 637,693 subjects, were collected and organized. Additionally, GWAS data for obesity, diabetes mellitus (DM), and smoking were obtained for further analysis. Single nucleotide polymorphisms (SNPs) significantly associated with the exposure factors (blood proteins) were selected to ensure their independence from other confounding factors and outcomes (CRC onset), and that they only affected outcomes through blood proteins. The causal effects of Mendelian Randomization (MR) were primarily estimated using the inverse variance weighted (IVW) method, with other methods serving as supplementary approaches. The Cochran's Q-test assessed heterogeneity among SNP estimates; the MR Egger method evaluated pleiotropy; and the leave-one-out test examined the sensitivity of individual SNPs. Obesity, DM, and smoking were included in the multivariate MR analysis.

A total of 31 SNPs and 8 blood protein exposure factors were identified, specifically TNFRSF16 (4 SNPs), RNF8 (4 SNPs), MRM3 (4 SNPs), ST6GALNAC1 (4 SNPs), TIE1 (4 SNPs), CBP (4 SNPs), DNAJB9 (4 SNPs), and EDN2 (3 SNPs). The IVW results showed a significant causal relationship between all 8 exposure factors and colorectal cancer (P < 0.05). Among these, TNFRSF16, TIE1, and EDN2 were identified as risk factors, while the remaining five served as protective factors. The causal inference in this study was not influenced by pleiotropy or environmental factors such as obesity, diabetes, and smoking. Therefore, the results were both stable and reliable.

Eight blood proteins (or genes) have been identified as having a causal relationship with the onset of colorectal cancer, suggesting their potential use as screening biomarkers and treatment targets.

Ovarian cancer is one of the leading causes of mortality among women worldwide. However, early detection can significantly reduce mortality rates and mitigate subsequent complications related to both economic burden and mental well-being. Despite the development in the field of medical diagnosis, the death rates due to ovarian cancer have sharply increased. Among the recent technologies suggested as suitable diagnostic techniques for the early detection of ovarian cancer, biosensor technology has emerged as a cutting-edge technology, with electrochemical biosensors providing one of the most efficient types of biosensors. Therefore, this review discusses the application of electrochemical biosensors as a viable alternative to conventional diagnostic techniques for the timely identification of ovarian cancer, its advantages over other types of biosensors and conventional diagnostic techniques, and the types of electrochemical biosensors.

Fecal DNA-based Syndecan 2 (SDC2) methylation detection is a promising non-invasive strategy for early colorectal cancer (CRC) screening. In China, commercial assays for SDC2 methylation detection vary in sensitivity and specificity, yet there is no standardized external quality assessment (EQA) to ensure accuracy. This study utilized CRISPR-Cas9 and homology-directed repair (HDR) technologies to edit the SDC2 promoter in 293T cells, creating hypermethylated and heterogeneous cell lines. These cell lines were used to develop an EQA panel for SDC2 methylation. We established a 10-sample panel, encompassing a range of methylation levels, and conducted an EQA across 140 laboratories. Among 1,400 results, 0.57% were incorrect. The optimized EQA materials effectively monitor the accuracy of SDC2 methylation detection in CRC, supporting reliable and consistent clinical testing and contributing to early CRC screening and diagnosis in China.

Non-small cell lung cancer (NSCLC) is the most common and deadly type of lung cancer, and its poor prognosis is closely related to the complex interactions of the tumor microenvironment. Through methylation analysis of tumor tissue samples from NSCLC patients, combined with high-throughput sequencing technology, the methylation status and structural characteristics of mRNA molecules were studied. Bioinformatics tools were used to analyze the regulatory effects of methylation modification on mRNA expression and genes associated with the tumor microenvironment. The results showed that the methylation level of specific mRNA was significantly correlated with the expression changes of tumor microenvironment-related factors. In addition, methylation modification affected mRNA stability and translation efficiency, further altering the metabolic activity and immune escape capacity of tumor cells. The results showed that mRNA with high methylation level was significantly associated with poor prognosis. Methylation modification profoundly affects the tumor microenvironment and prognosis of non-small cell lung cancer by altering the structure and function of mRNA molecules.

Methylated stool DNA (sDNA) is a reliable noninvasive biomarker for early colorectal cancer (CRC) diagnosis. However, there are barely any diagnostic panels that can achieve both a sensitivity and specificity exceeding 90% simultaneously.

We aimed to identify a novel methylated sDNA panel and model for the early diagnosis of CRC.

We conducted methyl-CpG binding domain isolated genome sequencing (MiGS) on CpG island methylation phenotype (CIMP)-positive (n = 3) and CIMP-negative CRC tissues (n = 3) and their corresponding normal adjacent tissues. Subsequently, by utilizing both the aforementioned data and public datasets, we identified a set of promising methylated sDNA markers for CRC. Next, we validated 5 of these genes using pyrosequencing in CRC patients (n = 31). Then, we developed a combined diagnostic model (CDM) for CRC based on the methylation status of PRDM12, FOXE1, and SDC2 by a Training cohort (n = 231). Finally, the performance of CDM was evaluated in an independent multicenter Validation cohort (n = 800).

A total of 1062 participants were included in this study. The area under the curve (AUC) of the CDM was 0.979 (95% CI: 0.960-0.997), and the optimal sensitivity and specificity were 97.35% and 99.05%, respectively, in the training cohort (n = 231). In the independent validation cohort (n = 800), the AUC was 0.950 (95% CI: 0.927-0.973), along with the optimal sensitivity of 92.75% and specificity of 97.21%. When CRC and advanced adenoma (AAD) were used as diagnostic targets, the model AUC was 0.945 (95% CI: 0.922-0.969), with an optimal sensitivity of 91.89% and a specificity of 95.21%. The model sensitivity for nonadvanced adenoma patients was 68.66%.

The sDNA diagnostic model CDM, developed from both CIMP-P and CIMP-N, exhibited exceptional performance in CRC and could serve as a potential alternative strategy for CRC screening.

Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. Platinum-based drugs, such as cisplatin and oxaliplatin, are frontline chemotherapy for CRC, effective in both monotherapy and combination regimens. However, the clinical efficacy of these treatments is often undermined by the development of drug resistance, a significant obstacle in cancer therapy. In recent years, epigenetic alterations have been recognized as key players in the acquisition of resistance to platinum drugs. Targeting these dysregulated epigenetic mechanisms with small molecules represents a promising therapeutic strategy. This review explores the complex relationship between epigenetic changes and platinum resistance in CRC, highlighting current epigenetic therapies and their effectiveness in countering resistance mechanisms. By elucidating the epigenetic underpinnings of platinum resistance, this review aims to contribute to ongoing efforts to improve treatment outcomes for CRC patients.

Colorectal cancer is a public health issue and was the third leading cause of cancer-related death worldwide in 2022. Early diagnosis can improve prognosis, making screening a central part of colorectal cancer management. Blood-based screening, diagnosis and follow-up of colorectal cancer patients are possible with the study of cell-free circulating tumor DNA. This study aimed to identify novel DNA methylation biomarkers of colorectal cancer that can be used for the follow-up of patients with colorectal cancer.

A DNA methylation profile was established in the Gene Expression Omnibus (GEO) database (n = 507) using bioinformatics analysis and subsequently confirmed using The Cancer Genome Atlas (TCGA) database (n = 348). The in silico profile was then validated on local tissue and cell-free DNA samples using methylation-specific digital PCR in colorectal cancer patients (n = 35) and healthy donors (n = 35).

The DNA methylation of COL25A1 and METAP1D was predicted to be a colorectal cancer biomarker by bioinformatics analysis (ROC AUC = 1, 95% CI [0.999-1]). The two biomarkers were confirmed with tissue samples, and the combination of COL25A1 and METAP1D yielded 49% sensitivity and 100% specificity for cell-free DNA.

Bioinformatics analysis of public databases revealed COL25A1 and METAP1D DNA methylation as clinically applicable liquid biopsies DNA methylation biomarkers. The specificity implies an excellent positive predictive value for follow-up, and the high sensitivity and relative noninvasiveness of a blood-based test make these biomarkers compatible with colorectal cancer screening. However, the clinical impact of these biomarkers in colorectal cancer screening and follow-up needs to be established in further prospective studies.

This cross-sectional study measured retinal vessel density (VD) in patients with digestive tract malignancy by optical coherence tomography angiography (OCTA), and compared them with healthy controls to explore the retinal microcirculation changes in patients with digestive tract malignancy.

106 eligible participants were divided into three groups: gastric cancer (GC) group (36 individuals), colorectal cancer (CRC) group (34 individuals), and healthy control group (36 individuals). Angio 6 × 6 512 × 512 R4 and ONH Angio 6 × 6 512 × 512 R4 modes were performed to collect retinal vessel density data centered on fovea and papillary, respectively. The retina was automatically segmented into different layers (superficial vascular plexus (SVP), the inner retinal layer, radial peripapillary capillary plexus (RPCP), deep vascular plexus (DVP)) and areas to analyze.

At the optic nerve head (ONH) region, the VD of the inner retinal layer increased in both GC and CRC groups in all quadrants and areas. In the papillary area, VD in the inner retinal layer, SVP, and RPCP increased in the GC and CRC groups. In the parapapillary area, VD in the inner retinal layer increased in the GC and the CRC groups. Significant increase in the global VD were found in the GC group of the RPCP and SVP. Regarding the macular region, no statistical differences were observed in each layer.

The study suggested that retinal vessel density changed in patients with digestive tract malignancy, especially in the inner retinal layer of the ONH region, revealing the potential relevance of the relation between gastrointestinal cancer and retinal microcirculation.

Gene methylation and the immune-related tumor microenvironment (TME) are highly correlated in tumor progression and therapeutic efficacy. Although both of them can be used to predict the clinical outcomes of colorectal cancer (CRC) patients, their predictive value is still unsatisfactory. Whether a combination risk model comprising these two prediction parameters performs better predictive effectiveness than independent factor is still unclear. Methylated Septin9 (mSEPT9) is an early diagnosis biomarker of CRC, in this study, we aimed to investigate mSEPT9-related biomarkers of immunosuppressive TME and identify the value of the combination risk model in predicting the clinical outcomes of CRC.

Immunofluorescence staining was performed to clarify the correlation between intratumoral IL-10+ Treg infiltration and mSEPT9 in peripheral blood. Survival time, response to 5-fluorouracil (5-FU)-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis were analyzed in study (197 CRC samples) and validation (195 CRC samples) sets to evaluate the efficacy of combination risk model. Potential mechanisms were explored by mRNA sequencing.

Hypermethylated SEPT9 in the peripheral blood of patients with CRC (stage I-III, and stage IV with resectable M1) before radical resection was positively correlated with high intratumoral IL-10+ Treg infiltration. The high-risk model revealed poor overall survival and progression-free survival, inferior therapeutic response to 5-FU-based chemotherapy and PD-1 blockade, and high probability of recurrence or metastasis. The underlying mechanisms may be associated with the increase in mSEPT9 and mediation of IL-10 via methionine metabolic reprogramming-induced infiltration of IL-10+ Tregs in the TME, which promotes tumor progression and resistance to 5-FU-based chemotherapy and PD-1 blockade.

The combination risk model of peripheral mSETP9 and intratumoral IL-10+ Treg infiltration in CRC can effectively predict prognosis, responsiveness to 5-FU-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis. Therefore, this model can be used for precision treatment of CRC.

Cancer-associated fibroblasts (CAFs), as key cell populations in the tumor microenvironment (TME), play a crucial role in tumor regulation. Previous studies on a prognostic signature of 8 CAF-related genes in head and neck squamous cell carcinoma (HNSCC) revealed that Secreted frizzled-related protein 1 (SFRP1) is one of the hub genes closely related to CAFs. SFRP1 is deficiently expressed in numerous types of cancer and is classified as a tumor suppressor gene. However, the role of SFRP1 in TME regulation in HNSCC remains unclear. This study aimed to explore the role of SFRP1 in the proliferation and migration of HNSCC cells by mediating CAFs and their regulatory mechanisms.

The expression differences, prognosis, and immune infiltration of SFRP1 in HNSCC were analyzed using the TIMER and GEPIA2 databases. The expression of SFRP1 in HNSCC tumor tissues, as well as the expression and secretion of SFRP1 in CAFs and tumor cells, were examined. An indirect co-culture system was constructed to detect the proliferation, migration, and apoptosis of HNSCC cells, and to clarify the effect of SFRP1 on tumor cells by mediating CAFs. Furthermore, the expression and secretion of 10 cytokines derived from CAFs that act on immune cells were verified.

SFRP1 was differently expressed in HNSCC tumor tissues and highly expressed in CAFs. SFRP1 inhibited the proliferation and migration of tumor cells and promoted apoptosis by mediating CAFs. The detection of CAFs-derived factors suggested that the mechanism of action of SFRP1 was associated with the regulation of immune cells.

SFRP1 inhibits the proliferation and migration of HNSCC cells by mediating CAFs, and the mechanism of action is related to the regulation of immune cells, which may provide new research directions and therapeutic targets for HNSCC.

While genome-wide association studies are valuable in identifying CRC survival predictors, the benefit of adding blood DNA methylation (blood-DNAm) to clinical features, including the TNM system, remains unclear. In a multi-site population-based patient cohort study of 2116 CRC patients with baseline blood-DNAm, we analyzed survival predictions using eXtreme Gradient Boosting with a 5-fold nested leave-sites-out cross-validation across four groups: traditional and comprehensive clinical features, blood-DNAm, and their combination. Model performance was assessed using time-dependent ROC curves and calibrations. During a median follow-up of 10.3 years, 1166 patients died. Although blood-DNAm-based predictive signatures achieved moderate performances, predictive signatures based on clinical features outperformed blood-DNAm signatures. The inclusion of blood-DNAm did not improve survival prediction over clinical features. M1 stage, age at blood collection, and N2 stage were the top contributors. Despite some prognostic value, incorporating blood DNA methylation did not enhance survival prediction of CRC patients beyond clinical features.

PANoptosis induces programmed cell death (PCD) through extensive crosstalk and is associated with development of cancer. However, the functional mechanisms, clinical significance, and potential applications of PANoptosis-related genes (PRGs) in colorectal cancer (CRC) have not been fully elucidated. Functional enrichment of key PRGs was analyzed based on databases, and relationships between key PRGs and the immune microenvironment, immune cell infiltration, chemotherapy drug sensitivity, tumor progression genes, single-cell cellular subgroups, signal transduction pathways, transcription factor regulation, and miRNA regulatory networks were systematically explored. This study identified 5 key PRGs associated with CRC: BCL10, CDKN2A, DAPK1, PYGM and TIMP1. Then, RT-PCR was used to verify expression of these genes in CRC cells and tissues. Clinical significance and prognostic value of key genes were further verified by multiple datasets. Analyses of the immune microenvironment, immune cell infiltration, chemotherapy drug sensitivity, tumor progression genes, single-cell cellular subgroups, and signal transduction pathways suggest a close relationship between these key genes and development of CRC. In addition, a novel prognostic nomogram model for CRC was successfully constructed by combining important clinical indicators and the key genes. In conclusion, our findings offer new insights for understanding the pathogenesis of CRC, predicting CRC prognosis, and identifying multiple therapeutic targets for future CRC therapy.

Cancer is the second leading cause of death worldwide and disease burden is expected to increase globally throughout the next several decades, with the majority of cancer-related deaths occurring in metastatic disease. Cancers exhibit known hallmarks that endow them with increased survival and proliferative capacities, frequently as a result of de-stabilizing mutations. However, the genomic features that resolve metastatic clones from primary tumors are not yet well-characterized, as no mutational landscape has been identified as predictive of metastasis. Further, many cancers exhibit no known mutation signature. This suggests a larger role for non-mutational genome re-organization in promoting cancer evolution and dissemination. In this review, we highlight current critical needs for understanding cell state transitions and clonal selection advantages for metastatic cancer cells. We examine links between epigenetic states, genome structure, and misregulation of tumor suppressors and oncogenes, and discuss how recent technologies for understanding domain-scale regulation have been leveraged for a more complete picture of oncogenic and metastatic potential.

Kirsten Rat Sarcoma (KRAS) is the most commonly mutated oncogene in colorectal carcinoma (CRC). We have previously reported the interactions between microsatellite instability (MSI), DNA promoter methylation, and gene expression. In this study, we looked for associations between KRAS mutation, gene expression, and methylation that may help with precision medicine. Genome-wide gene expression and DNA methylation were done in paired CRC tumor and surrounding healthy tissues. The results suggested that (a) the magnitude of dysregulation of many major gene pathways in CRC was significantly greater in patients with the KRAS mutation, (b) the up- and down-regulation of these dysregulated gene pathways could be correlated with the corresponding hypo- and hyper-methylation, and (c) the up-regulation of CDKN2A was more pronounced in tumors with the KRAS mutation. A recent cell line study showed that there were higher CDKN2A levels in 5-FU-resistant CRC cells and that these could be down-regulated by Villosol. Our findings suggest the possibility of a better response to anti-CDKN2A therapy with Villosol in KRAS-mutant CRC. Also, the more marked up-regulation of genes in the proteasome pathway in CRC tissue, especially with the KRAS mutation and MSI, may suggest a potential role of a proteasome inhibitor (bortezomib, carfilzomib, or ixazomib) in selected CRC patients if necessary.

Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development.

To construct a robust prognostic signature, we used developed and validated across datasets.

After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted.

In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples.

The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.

The resistance of colorectal cancer (CRC) to conventional therapeutic modalities, such as radiation therapy and chemotherapy, along with the associated side effects, significantly limits effective anticancer strategies. Numerous epigenetic investigations have unveiled that naturally occurring stilbenes can modify or reverse abnormal epigenetic alterations, particularly aberrant DNA methylation status, offering potential avenues for preventing or treating CRC. By modulating the activity of the DNA methylation machinery components, phytochemicals may influence the various stages of CRC carcinogenesis through multiple molecular mechanisms. Several epigenetic studies, especially preclinical research, have highlighted the effective DNA methylation modulatory effects of stilbenes with minimal adverse effects on organisms, particularly in combination therapies for CRC. However, the available preclinical and clinical data regarding the effects of commonly encountered stilbenes against CRC are currently limited. Therefore, additional epigenetic research is warranted to explore the preventive potential of these phytochemicals in CRC development and to validate their therapeutic application in the prevention and treatment of CRC. This review aims to provide an overview of selected bioactive stilbenes as potential chemopreventive agents for CRC with a focus on their modulatory mechanisms of action, especially in targeting alterations in DNA methylation machinery in CRC.

Telomere length (TL) is an important indicator of cellular aging. Shorter TL is associated with several age-related diseases including coronary heart disease, heart failure, diabetes, osteoporosis, and cancer. Recently, a DNA methylation-based TL (DNAmTL) estimator has been developed as an alternative method for directly measuring TL. In this study, we examined the association of DNAmTL with cancer prevalence and mortality risk among people with and without HIV in the Veterans Aging Cohort Study Biomarker Cohort (VACS, N = 1917) and Women's Interagency HIV Study Cohort (WIHS, N = 481). We profiled DNAm in whole blood (VACS) or in peripheral blood mononuclear cells (WIHS) using an array-based method. Cancer prevalence was estimated from electronic medical records and cancer registry data. The VACS Index was used as a measure of physiologic frailty. Models were adjusted for self-reported race and ethnicity, batch, smoking status, alcohol consumption, and five cell types (CD4, CD8, NK, B cell, and monocyte). We found that people with HIV had shorter average DNAmTL than those without HIV infection [beta = -0.25, 95% confidence interval (-0.32, -0.18), p = 1.48E-12]. Greater value of VACS Index [beta = -0.002 (-0.003, -0.001), p = 2.82E-05] and higher cancer prevalence [beta = -0.07 (-0.10, -0.03), p = 1.37E-04 without adjusting age] were associated with shortened DNAmTL. In addition, one kilobase decrease in DNAmTL was associated with a 40% increase in mortality risk [hazard ratio: 0.60 (0.44, 0.82), p = 1.42E-03]. In summary, HIV infection, physiologic frailty, and cancer are associated with shortening DNAmTL, contributing to an increased risk of all-cause mortality.

Epigenetics play a vital role in stratifying CNS tumors and gliomas. The importance of studying Secreted frizzled-related protein 4 (SFRP4) in gliomas is to improve diffuse glioma methylation profiling. Here we examined the methylation status of SFRP4 promoter and the level of its protein expression in diffuse gliomas WHO grades 2-4.

SFRP4 expression was detected by immunohistochemistry and evaluated semi-quantitatively. In the tumor hot-spot area, the intensity of protein expression in 200 cells was determined using ImageJ (National Institutes of Health, United States). The assessment of immunopositivity was based on the IRS score (Immunoreactivity Score). Promoter methylation was examined by methylation specific-PCR (MSP) in fifty-one diffuse glioma samples and appropriate controls. Isolated DNA was treated with bisulfite conversion and afterwards used for MSP. Public databases (cBioPortal, COSMIC and LOVD) were searched to corroborate the results.

SFRP4 protein expression in glioblastomas was very weak or non-existent in 86.7% of samples, moderate in 13.3%, while strong expression was not observed. The increase in astrocytoma grade resulted in SFRP4 protein decrease (p = 0.008), indicating the loss of its antagonistic role in Wnt signaling. Promoter methylation of SFRP4 gene was found in 16.3% of cases. Astrocytomas grade 2 had significantly more methylated cases compared to grade 3 astrocytomas (p = 0.004) and glioblastomas (p < 0.001), which may indicate temporal niche of methylation in grade 2. Furthermore, the expression levels of SFRP4 were high in samples with methylated SFRP4 promoter and low or missing in unmethylated cases (Pearson's R = -0.413; p = 0.003). We also investigated the association of SFRP4 changes to key Wnt regulators GSK3β and DKK3 and established a positive correlation between methylations of SFRP4 and GSK3β (Pearson's R = 0.323; p = 0.03). Furthermore, SFRP4 expression was correlated to unmethylated DKK3 (Chi square = 7.254; p = 0.027) indication that Wnt signaling antagonist is associated to negative regulator's demethylation.

The study contributes to the recognition of the significance of epigenetic changes in diffuse glioma indicating that restoring SFRP4 protein holds potential as therapeutic avenue. Reduced expression of SFRP4 in glioblastomas, not following promoter methylation pattern, suggests another mechanism, possible global methylation, that turns off SFRP4 expression in higher grades.

Bronchoscopic-assisted discrimination of lung tumors presents challenges, especially in cases with contraindications or inaccessible lesions. Through meta-analysis and validation using the HumanMethylation450 database, this study identified methylation markers for molecular discrimination in lung tumors and designed a sequencing panel. DNA samples from 118 bronchial washing fluid (BWF) specimens underwent enrichment via multiplex PCR before targeted methylation sequencing. The Recursive Feature Elimination Cross-Validation and deep neural network algorithm established the CanDo classification model, which incorporated 11 methylation features (including 8 specific to the TBR1 gene), demonstrating a sensitivity of 98.6% and specificity of 97.8%. In contrast, bronchoscopic rapid on-site evaluation (bronchoscopic-ROSE) had lower sensitivity (87.7%) and specificity (80%). Further validation in 33 individuals confirmed CanDo's discriminatory potential, particularly in challenging cases for bronchoscopic-ROSE due to pathological complexity. CanDo serves as a valuable complement to bronchoscopy for the discriminatory diagnosis and stratified management of lung tumors utilizing BWF specimens.

The prognosis for patients with colorectal cancer (CRC) remains worse than expected due to metastasis, recurrence, and resistance to chemotherapy. Colorectal cancer stem cells (CRCSCs) play a vital role in tumor metastasis, recurrence, and chemotherapy resistance. However, there are currently no prognostic markers based on CRCSCs-related genes available for clinical use. In this study, single-cell transcriptome sequencing was employed to distinguish cancer stem cells (CSCs) in the CRC microenvironment and analyze their properties at the single-cell level. Subsequently, data from TCGA and GEO databases were utilized to develop a prognostic risk model for CRCSCs-related genes and validate its diagnostic performance. Additionally, functional enrichment, immune response, and chemotherapeutic drug sensitivity of the relevant genes in the risk model were investigated. Lastly, the key gene RPS17 in the risk model was identified as a potential prognostic marker and therapeutic target for further comprehensive studies. Our findings provide new insights into the prognostic treatment of CRC and offer novel perspectives for a systematic and comprehensive understanding of CRC development.

Vitamin B12 plays a role in DNA methylation, influencing the 1-carbon cycle; However, its effect on colorectal cancer (CRC) mortality remains uncertain. This study assessed the relationship between vitamin B12 intake and all-cause and cancer-specific mortality among CRC patients. We analyzed data from the NHANES from 1999 to 2018, using multivariable Cox regression, competing risk model, Kaplan-Meier survival curves, and stratified analysis with interaction effects. The studied involved 4,554 cancer patients (mean age 65.8 years, 47.6% males). Results from multivariate Cox regression indicated that each additional 1 mcg/day of dietary vitamin B12 independently increased the risk of all-cause (HR, 1.07; 95% CI: 1.04-1.09, p < 0.001) and cancer-specific mortality (HR, 1.04; 95% CI, 1.02-1.06; p < 0.001). Kaplan-Meier curves indicated a higher risk of all-cause mortality with increased vitamin B12 intake (Log rank p = 0.01). Subgroup analysis suggested that higher vitamin B12 intake correlated with increased all-cause mortality risk, especially in individuals with higher protein (HR, 1.04; 95% CI, 1.02-1.06; p = 0.019) or carbohydrate intake (HR, 1.03; 95% CI, 1.01-1.05; p = 0.04). Thus, higher vitamin B12 intake correlates with increased all-cause and cancer-specific mortality in CRC patients, particularly those with higher protein or carbohydrate intake.

Although cancer initiation and progression are generally associated with the accumulation of somatic mutations1,2, substantial epigenomic alterations underlie many aspects of tumorigenesis and cancer susceptibility3-6, suggesting that genetic mechanisms might not be the only drivers of malignant transformation7. However, whether purely non-genetic mechanisms are sufficient to initiate tumorigenesis irrespective of mutations has been unknown. Here, we show that a transient perturbation of transcriptional silencing mediated by Polycomb group proteins is sufficient to induce an irreversible switch to a cancer cell fate in Drosophila. This is linked to the irreversible derepression of genes that can drive tumorigenesis, including members of the JAK-STAT signalling pathway and zfh1, the fly homologue of the ZEB1 oncogene, whose aberrant activation is required for Polycomb perturbation-induced tumorigenesis. These data show that a reversible depletion of Polycomb proteins can induce cancer in the absence of driver mutations, suggesting that tumours can emerge through epigenetic dysregulation leading to inheritance of altered cell fates.

Colorectal cancer (CRC) is one of the deadliest malignancies worldwide, ranking third in incidence and second in mortality. Remarkably, early stage localized CRC has a 5-year survival rate of over 90%; in stark contrast, the corresponding 5-year survival rate for metastatic CRC (mCRC) is only 14%. Compounding this problem is the staggering lack of effective therapeutic strategies. Beyond genetic mutations, which have been identified as critical instigators of CRC initiation and progression, the importance of epigenetic modifications, particularly DNA methylation (DNAm), cannot be underestimated, given that DNAm can be used for diagnosis, treatment monitoring and prognostic evaluation. This review addresses the intricate mechanisms governing aberrant DNAm in CRC and its profound impact on critical oncogenic pathways. In addition, a comprehensive review of the various techniques used to detect DNAm alterations in CRC is provided, along with an exploration of the clinical utility of cancer-specific DNAm alterations.