SCTR hypermethylation is a diagnostic biomarker in colorectal cancer

DNA methylation modulates epigenetic regulation in colorectal cancer diagnosis, prognosis and precision medicine

Colorectal cancer (CRC) is a multifaceted disease influenced by the interplay of genetic and environmental factors. The clinical heterogeneity of CRC cannot be attributed exclusively to genetic diversity and environmental exposures, and epigenetic markers, especially DNA methylation, play a critical role as key molecular markers of cancer. This review compiles a comprehensive body of evidence underscoring the significant involvement of DNA methylation modifications in the pathogenesis of CRC. Moreover, this review explores the potential utility of DNA methylation in cancer diagnosis, prognostics, assessment of disease activity, and prediction of drug responses. Recognizing the impact of DNA methylation will enhance the ability to identify distinct CRC subtypes, paving the way for personalized treatment strategies and advancing precision medicine in the management of CRC.

Integrated analysis of multi-omics data for the discovery of biomarkers and therapeutic targets for colorectal cancer

The considerable burden of colorectal cancer and the rising trend in young adults emphasize the necessity of understanding its underlying mechanisms, providing new diagnostic and prognostic markers, and improving therapeutic approaches. Precision medicine is a new trend all over the world and identification of novel biomarkers and therapeutic targets is a step forward towards this trend. In this context, multi-omics data and integrated analysis are being investigated to develop personalized medicine in the management of colorectal cancer. Given the large amount of data from multi-omics approach, data integration and analysis is a great challenge. In this Review, we summarize how statistical and machine learning techniques are applied to analyze multi-omics data and how it contributes to the discovery of useful diagnostic and prognostic biomarkers and therapeutic targets. Moreover, we discuss the importance of these biomarkers and therapeutic targets in the clinical management of colorectal cancer in the future. Taken together, integrated analysis of multi-omics data has great potential for finding novel diagnostic and prognostic biomarkers and therapeutic targets, however, there are still challenges to overcome in future studies.

Application of Polypyrrole-Based Electrochemical Biosensor for the Early Diagnosis of Colorectal Cancer

Although colorectal cancer (CRC) is easy to treat surgically and can be combined with postoperative chemotherapy, its five-year survival rate is still not optimistic. Therefore, developing sensitive, efficient, and compliant detection technology is essential to diagnose CRC at an early stage, providing more opportunities for effective treatment and intervention. Currently, the widely used clinical CRC detection methods include endoscopy, stool examination, imaging modalities, and tumor biomarker detection; among them, blood biomarkers, a noninvasive strategy for CRC screening, have shown significant potential for early diagnosis, prediction, prognosis, and staging of cancer. As shown by recent studies, electrochemical biosensors have attracted extensive attention for the detection of blood biomarkers because of their advantages of being cost-effective and having sound sensitivity, good versatility, high selectivity, and a fast response. Among these, nano-conductive polymer materials, especially the conductive polymer polypyrrole (PPy), have been broadly applied to improve sensing performance due to their excellent electrical properties and the flexibility of their surface properties, as well as their easy preparation and functionalization and good biocompatibility. This review mainly discusses the characteristics of PPy-based biosensors, their synthetic methods, and their application for the detection of CRC biomarkers. Finally, the opportunities and challenges related to the use of PPy-based sensors for diagnosing CRC are also discussed.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

Diagnostic genes and immune infiltration analysis of colorectal cancer determined by LASSO and SVM machine learning methods: a bioinformatics analysis

BACKGROUND

Genetic factors account for approximately 35% of colorectal cancer risk. The specificity and sensitivity of previous diagnostic biomarkers for colorectal cancer could not meet the need of clinical application. The expanding scale and inherent complexity of biological data have encouraged a growing use of machine learning to build informative and predictive models of the underlying biological processes. The aim of this study is to identify diagnostic genes of colorectal cancer by using machine learning methods.

METHODS

The GSE41328 and GSE106582 data sets were downloaded from the Gene Expression Omnibus (GEO) database. The gene expression differences between colon cancer and normal tissues were analyzed. The key colorectal cancer genes were screened and validated by Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) regression. Immune cell infiltration and the correlation with the key genes in patients with colon cancer were further analyzed by CIBERSORT.

RESULTS

Eleven key genes were identified as biomarkers for colon cancer, namely ASCL2, BEST4, CFD, DPEPCFD, FOXQ1, TRIB3, KLF4, MMP7, MMP11, PYY, and PDK4. The mean area under the receiver operating characteristic (ROC) curve (AUC) of all 11 genes for colon cancer diagnosis were 0.94 with a range of 0.91-0.97. In the validation set, the expression of the 11 key genes was significantly different between colon cancer and normal subjects (P<0.05) and the mean AUCs were 0.82 with a range of 0.70-0.88. Immune cell infiltration analyses demonstrated that the relative quantity of plasma cells, T cells, B cells, NK cells, MO, M1, Dendritic cells resting, Mast cells resting, Mast cells activated, and Neutrophils in the tumor group were significantly different to the normal group.

CONCLUSIONS

ASCL2, BEST4, CFD, DPEPCFD, FOXQ1, TRIB3, KLF4, MMP7, MMP11, PYY, and PDK4 were identified as the key genes for colon cancer diagnosis. These genes are expected to become novel diagnostic markers and targets of new pharmacotherapies for colorectal cancer.

Association of a Novel DOCK2 Mutation-Related Gene Signature With Immune in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality worldwide. Many studies have shown that dedicator of cytokinesis 2 (DOCK2) has a crucial role as a prognostic factor in various cancers. However, the potentiality of DOCK2 in the diagnosis of HCC has not been fully elucidated. In this work, we aimed to investigate the prognostic role of DOCK2 mutation in HCC. The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) cohorts were utilized to identify the mutation frequency of DOCK2. Then, univariate Cox proportional hazard regression analysis, random forest (RF), and multivariate Cox regression analysis were performed to develop the risk score that was significantly related to DOCK2 mutation. Moreover, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune correlation analysis were conducted for an in-depth study of the biological process of DOCK2 mutation involved in HCC. The results revealed that the mutation frequency of DOCK2 was relatively higher than that in non-cancer control subjects, and patients with DOCK2 mutations had a low survival rate and a poor prognosis compared with the DOCK2-wild group. In addition, the secretin receptor (SCTR), tetratricopeptide repeat, ankyrin repeat and coiled-coil domain-containing 1 (TANC1), Alkb homolog 7 (ALKBH7), FRAS1-related extracellular matrix 2 (FREM2), and G protein subunit gamma 4 (GNG4) were found to be the most relevant prognostic genes of DOCK2 mutation, and the risk score based on the five genes played an excellent role in predicting the status of survival, tumor mutation burden (TMB), and microsatellite instability (MSI) in DOCK2 mutant patients. In addition, DOCK2 mutation and the risk score were closely related to immune responses. In conclusion, the present study identifies a novel prognostic signature in light of DOCK2 mutation-related genes that shows great prognostic value in HCC patients; and this gene mutation might promote tumor progression by influencing immune responses. These data may provide valuable insights for future investigations into personalized forecasting methods and also shed light on stratified precision oncology treatment.

New Studies of the Aberrant Alterations in Fibrillin-1 Methylation During Colorectal Cancer Development

Background

Fibrillin-1 (FBN1) methylation risk from control to colorectal cancer (CRC), the variation regularities of FBN1 methylation, and DNA methyltransferase (DNMT) catalyzed with FBN1 methylation had not been reported yet; these were all studied in this paper.

Methods

FBN1 methylation roles were investigated with big data and meta-analysis.

Results

The 6 independent studies were searched including 702 tissue and 448 feces. FBN1 methylation frequencies of CRC, adenoma or polyp, and control in tissue were 79.1%, 69.4%, and 2.7%, respectively; those in feces were 74.6%, 50.7%, and 10.8%, respectively. FBN1 methylation of control samples was used as a standard reference; this study showed that ORs (95% CI) of FBN1 methylation in CRC and control tissues were 124.79 (62.86-248.35); those in feces were detected to be 30.87 (16.48-57.85). FBN1 methylation risk in tissue was higher than that in feces; there was a quadratic equation between the methylation rate of tissue and that of feces. There was another quadratic curve in the variation process of FBN1 methylation; this curve reflected the overall metabolism regularity of DNMT.

Conclusions

The transcriptional inactivation of FBN1 gene might start from normal colonic epithelium; the quadratic curve of FBN1 methylation catalyzed by DNMT can gradually produce powerful strength, accelerate expansion, and eventually lead to CRC. The overall metabolism regularity of DNMT maintains the changing process of FBN1 methylation; it has the changing feature of the same quadratic curve. FBN1 methylation is a promising biomarker. FBN1 methylation risk size in feces reflects that in tissue in non-invasive detection.

Dynamic liquid biopsy components as predictive and prognostic biomarkers in colorectal cancer

Colorectal cancer (CRC) is one of the most common cancers worldwide. The diagnosis, prognosis and therapeutic monitoring of CRC depends largely on tissue biopsy. However, due to tumor heterogeneity and limitations such as invasiveness, high cost and limited applicability in longitudinal monitoring, liquid biopsy has gathered immense attention in CRC. Liquid biopsy has several advantages over tissue biopsy including ease of sampling, effective monitoring, and longitudinal assessment of treatment dynamics. Furthermore, the importance of liquid biopsy is signified by approval of several liquid biopsy assays by regulatory bodies indicating the powerful approach of liquid biopsy for comprehensive CRC screening, diagnostic and prognostics. Several liquid biopsy biomarkers such as novel components of the microbiome, non-coding RNAs, extracellular vesicles and circulating tumor DNA are extensively being researched for their role in CRC management. Majority of these components have shown promising results on their clinical application in CRC including early detection, observe tumor heterogeneity for treatment and response, prediction of metastases and relapse and detection of minimal residual disease. Therefore, in this review, we aim to provide updated information on various novel liquid biopsy markers such as a) oral microbiota related bacterial network b) gut microbiome-associated serum metabolites c) PIWI-interacting RNAs (piRNAs), microRNA(miRNAs), Long non-coding RNAs (lncRNAs), circular RNAs (circRNAs) and d) circulating tumor DNAs (ctDNA) and circulating tumor cells (CTC) for their role in disease diagnosis, prognosis, treatment monitoring and their applicability for personalized management of CRC.

Differential DNA methylation analysis of SUMF2, ADAMTS5, and PXDN provides novel insights into colorectal cancer prognosis prediction in Taiwan

BACKGROUND

Patients with colorectal cancer (CRC) undergo surgery, as well as perioperative chemoradiation or adjuvant chemotherapy primarily based on the tumor–node– metastasis (TNM) cancer staging system. However, treatment responses and prognostic outcomes of patients within the same stage vary markedly. The potential use of novel biomarkers can improve prognostication and shared decision making before implementation into certain therapies.

AIM

To investigate whether SUMF2, ADAMTS5, and PXDN methylation status could be associated with CRC prognosis.

METHODS

We conducted a Taiwan region cohort study involving 208 patients with CRC recruited from Tri-Service General Hospital and applied the candidate gene approach to identify three genes involved in oncogenesis pathways. A methylation-specific polymerase chain reaction (MS-PCR) and EpiTYPER DNA methylation analysis were employed to detect methylation status and to quantify the methylation level of candidate genes in tumor tissue and adjacent normal tissue from participants. We evaluated SUMF2, ADAMTS5, and PXDN methylation as predictors of prognosis, including recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS), using a Cox regression model and Kaplan–Meier analysis.

RESULTS

We revealed various outcomes related to methylation and prognosis. Significantly shorter PFS and OS were associated with the CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue compared with CpG_3+CpG_7 hypomethylation [hazard ratio (HR) = 2.24, 95% confidence interval (CI) = 1.03-4.85 for PFS, HR = 2.56 and 95%CI = 1.08-6.04 for OS]. By contrast, a significantly longer RFS was associated with CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue compared with CpG_2 and CpG_13 hypomethylation [HR (95%CI) = 0.15 (0.03-0.71) for CpG_2 and 0.20 (0.04-0.97) for CpG_13]. The relationship between the methylation status of PXDN and the prognosis of CRC did not reach statistical significance.

CONCLUSION

Our study found that CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue was associated with significantly shorter PFS and OS compared with CpG_3+CpG_7 hypomethylation. CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue was associated with a significantly longer RFS compared with CpG_2 and CpG_13 hypomethylation. These methylation-related biomarkers which have implications for CRC prognosis prediction may aid physicians in clinical decision-making.

Secretin Receptor as a Target in Gastrointestinal Cancer: Expression Analysis and Ligand Development

Secretin was originally discovered as a gastrointestinal peptide that stimulates fluid secretion from the pancreas and liver and delays gastric emptying. In disease, a secretin receptor (SCTR) was found to occur as a splice variant in gastrinoma and pancreatic adenocarcinoma. Overexpression of SCTR has been described for gastrinomas, carcinoid tumors of the lung and cholangiocarcinoma. SCTR therefore is considered a candidate target for molecular tumor imaging as well as for peptide receptor radioligand therapy (PRRT) in a number of oncological indications. The aim of this study was to characterize SCTR expression in esophageal and pancreatic cancer, demonstrating for the first time high SCTR overexpression in these tumor types. In total, 65 of 70 pancreatic ductal adenocarcinoma tissues stained strongly positive for SCTR in immunohistochemistry, as did most of the 151 esophageal cancer samples, with minor influence of grading in both entities. In addition, the aim of this study was to further delineate residues in human secretin that are critical for binding to and activation of human SCTR. For a potential development of short and metabolically stable analogs for clinical use, it was intended to probe the peptide for its capacity to incorporate deletions and substitutions without losing its affinity to SCTR. In a systematic approach, a library of 146 secretin variants containing single amino acid substitutions as well as truncations on either end was tested in β-arrestin2-GFP translocation and fluorescent ligand internalization assays employing high-content analysis, in cAMP assays which run in agonist and antagonist mode, and in radioligand binding. The main structural determinants of SCTR binding and activation were localized to the N-terminus, with His1, Asp3 being among the most sensitive positions, followed by Phe6, Thr7 and Leu10. Aminoterminal truncation caused a rapid decline in receptor activity and most of these variants proved to be partial agonists showing antagonistic properties. In this study, the most potent novel antagonist showed an IC50 of 309 ± 74 nM in the β-arrestin2-GFP translocation assay on human SCTR while remaining a weak partial agonist. Future studies will have to demonstrate the utility of further enhanced secretin analogues as tracers for in vivo imaging and therapy.

Biological applications of chiral inorganic nanomaterials

Chirality is common in nature and plays the essential role in maintaining physiological process. Chiral inorganic nanomaterials with intense optical activity have attracted more attention due to amazing properties in recent years. Over the past decades, many efforts have been paid to the preparation and chirality origin of chiral nanomaterials; furthermore, emerging biological applications have been investigated widely. This review mainly summarizes recent advances in chiral nanomaterials. The top-down and bottom-up preparation methods and chirality origin of chiral nanomaterials are introduced; besides, the biological applications, such as sensing, therapy, and catalysis, will be introduced comprehensively. Finally, we also provide a perspective on the biomedical applications of chiral nanomaterials.

TSHZ3 functions as a tumor suppressor by DNA methylation in colorectal cancer

OBJECTIVE

Teashirt zinc finger homeobox 3 (TSHZ3) is currently reported to be aberrantly expressed in several tumors, but the detailed functions and epigenetic mechanisms of TSHZ3 in colorectal cancer (CRC) remain unclear.

MATERIALS AND METHODS

In this study, the TSHZ3 expression in 118 CRC and normal adjacent tissues (NATs) was evaluated, and the methylation status of the TSZH3 promoter region in CRC tissues and cell lines was also analyzed.

RESULTS

The results of PCR analysis showed that TSHZ3 was significantly down-regulated in CRC tissues, and patients with low TSHZ3 levels had a poorer 5-year overall survival (OS) rate. Analyzing the promoter sequence (-1000∼0) by MethPrimer, TSHZ3 promoter was found to harbor abundant of CpG islands. The methylation specific PCR (MSP) analysis presented a relatively hypermethylated status of THSZ3 promoter in CRC samples. The data of MSP and bisulfite sequencing PCR (BSP) also confirmed that CpG sites of TSHZ3 promoter were methylated in CRC cells, and the DNA methyltransferase (DNMT) inhibitor 5-aza-2'-deoxycytidine (5-Aza) could effectively restored the TSHZ3 expression in vitro. Functionally, the proliferation, apoptosis and metastasis of CRC cells were regulated by TSZH3 over-expression, and the suppressing effects of TSHZ3 in CRC were also confirmed in a xenograft mouse model.

CONLUSIONS

Our results indicated that promoter methylation was one of the mechanisms contributing to the down-regulation of TSHZ3 in CRC, and TSZH3 might served as a potential tumor suppressor gene in the development and progression of CRC.

Promising Epigenetic Biomarkers for the Early Detection of Colorectal Cancer: A Systematic Review

In CRC, screening compliance is decreased due to the experienced discomfort associated with colonoscopy, although this method is the gold standard in terms of sensitivity and specificity. Promoter DNA methylation (hypomethylation or hypermethylation) has been linked to all CRC stages. Study objectives: to systematically review the current knowledge on approved biomarkers, reveal new potential ones, and inspect tactics that can improve performance. This research was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines; the risk of bias was evaluated using the revised Quality Assessment of Diagnostic Accuracy Studies criteria (QUADAS-2). The Web of Science® Core Collection, MEDLINE® and Scopus® databases were searched for original articles published in peer-reviewed journals with the specific keywords "colorectal cancer", "early detection", "early-stage colorectal cancer", "epigenetics", "biomarkers", "DNA methylation biomarkers", "stool or blood or tissue or biopsy", "NDRG4", "BMP3", "SEPT9", and "SDC2". Based on eligibility criteria, 74 articles were accepted for analysis. mSDC2 and mSEPT9 were frequently assessed in studies, alone or together as part of the ColoDefense panel test-the latter with the greatest performance. mBMP3 may not be an appropriate marker for detecting CRC. A panel of five methylated binding sites of the CTCF gene holds the promise for early-stage specific detection of CRC. CRC screening compliance and accuracy can be enhanced by employing a stool mt-DNA methylation test.

Identification of a Novel Immune-Related CpG Methylation Signature to Predict Prognosis in Stage II/III Colorectal Cancer

With the increasing incidence of colorectal cancer (CRC) and continued difficulty in treating it using immunotherapy, there is an urgent need to identify an effective immune-related biomarker associated with the survival and prognosis of patients with this disease. DNA methylation plays an essential role in maintaining cellular function, and changes in methylation patterns may contribute to the development of autoimmunity, aging, and cancer. In this study, we aimed to identify a novel immune-related methylated signature to aid in predicting the prognosis of patients with CRC. We investigated DNA methylation patterns in patients with stage II/III CRC using datasets from The cancer genome atlas (TCGA). Overall, 182 patients were randomly divided into training (n = 127) and test groups (n = 55). In the training group, five immune-related methylated CG sites (cg11621464, cg13565656, cg18976437, cg20505223, and cg20528583) were identified, and CG site-based risk scores were calculated using univariate Cox proportional hazards regression in patients with stage II/III CRC. Multivariate Cox regression analysis indicated that methylated signature was independent of other clinical parameters. The Kaplan-Meier analysis results showed that CG site-based risk scores could significantly help distinguish between high- and low-risk patients in both the training (P = 0.000296) and test groups (P = 0.022). The area under the receiver operating characteristic curve in the training and test groups were estimated to be 0.771 and 0.724, respectively, for prognosis prediction. Finally, stratified analysis results suggested the remarkable prognostic value of CG site-based risk scores in CRC subtypes. We identified five methylated CG sites that could be used as an efficient overall survival (OS)-related biomarker for stage II/III CRC patients.

SCTR hypermethylation is a diagnostic biomarker in colorectal cancer

Diagnostic markers for both colorectal cancer (CRC) and its precursor lesions are lacking. Although aberrant methylation of the secretin receptor (SCTR) gene was observed in CRC, the diagnostic performance has not been evaluated. Therefore, this study aimed to assess and verify the diagnostic value of SCTR methylation of CRC and its precursor lesions through integrating the largest methylation data. The diagnostic performance of SCTR methylation was analyzed in the discovery set from The Cancer Genome Atlas (TCGA) CRC methylation data (N = 440), and verified in a large-scale test set (N = 938) from the Gene Expression Omnibus (GEO). Targeted bisulfite sequencing analysis was developed and applied to detect the methylation status of SCTR in our independent validation set (N = 374). Our findings revealed that the SCTR gene was frequently hypermethylated at its CpG islands in CRC. In the TCGA discovery set, the diagnostic score was constructed using 4 CpG sites (cg01013590, cg20505223, cg07176264, and cg26009192) and achieved high diagnostic performance (area under the ROC curve [AUC] = 0.964). In the GEO test set, the diagnostic score had robust diagnostic ability to distinguish CRC (AUC = 0.948) and its precursor lesions (AUC = 0.954) from normal samples. Moreover, hypermethylation of the SCTR gene was also found in cell-free DNA samples collected from CRC patients, but not in those from healthy controls. In the validation set, consistent results were observed using the targeted bisulfite sequencing array. Our study highlights that hypermethylation at CpG islands of the SCTR gene is a potential diagnostic biomarker in CRCs and its precursor lesions.