Advances in CpG Island Methylator Phenotype Colorectal Cancer Therapies

Redefining Therapeutic Approaches in Colorectal Cancer: Targeting Molecular Pathways and Overcoming Resistance

Colorectal cancer (CRC) arises through a combination of genetic and epigenetic alterations that affect key pathways involved in tumor growth and progression. This review examines the major molecular pathways driving CRC, including Chromosomal Instability (CIN), Microsatellite Instability (MSI), and the CpG Island Methylator Phenotype (CIMP). Key mutations in genes such as APC, KRAS, NRAS, BRAF, and TP53 activate signaling pathways like Wnt, EGFR, and PI3K/AKT, contributing to tumorigenesis and influencing responses to targeted therapies. Resistance mechanisms, including mutations that bypass drug action, remain challenging in CRC treatment. This review highlights the role of molecular profiling in guiding the use of targeted therapies such as tyrosine kinase inhibitors and immune checkpoint inhibitors. Novel combination treatments are also discussed as strategies to improve outcomes and overcome resistance. Understanding these molecular mechanisms is critical to advancing personalized treatment approaches in CRC and improving patient prognosis.

Early colorectal cancer diagnosis: A novel methylated stool DNA model enhanced the diagnostic efficiency

BACKGROUND

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.

OBJECTIVE

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

METHODS

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).

RESULTS

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%.

CONCLUSION

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.

Deep learning-based histological predictions of chromosomal instability in colorectal cancer

Colorectal cancer (CRC) is a lethal malignancy and a leading cause of cancer-related mortality worldwide. Chromosomal instability (CIN) is a key driver of genomic instability in CRC and is characterized by aneuploidy and somatic copy-number alterations. This study aimed to predict CIN in CRC using histological data from whole slide images (WSIs). CRC samples from TCGA were analyzed, with tumor regions segmented into tiles and nuclei for feature extraction using convolutional neural network (CNN) and morphologic analysis. Binary classification models were developed to distinguish high and low aneuploidy scores (AS) based on slide-level features. The analysis included 313 patients with 315 WSIs, resulting in over 350,000 tumor tiles and nearly 2.7 million tumor cell nuclei. The ResNet18-SSL model, pre-trained on histopathological images, demonstrated superior accuracy in tile-based AS prediction, while DenseNet121 excelled in nucleus-based prediction. Combining CNN-based and morphological features enhanced the classification accuracy of nucleus-based predictions. Additionally, significant correlations were observed between morphological features and copy-number signatures. Unsupervised clustering of nuclear features revealed that distinct groups are significantly correlated with CIN and TP53 mutations. This study underscores the potential of histological features from WSIs to predict CIN in CRC samples. Nuclear feature analysis, combined with deep-learning techniques, offers a robust method for CIN prediction, highlighting the importance of further research into the relationships between histological and molecular phenotypes.

Natural Stilbenes: Their Role in Colorectal Cancer Prevention, DNA Methylation, and Therapy

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.

Unmasking early colorectal cancer clues: in silico and in vitro investigation of downregulated IGF2, SOCS1, MLH1, and CACNA1G in SSA polyps

BACKGROUND AND AIM

Colorectal cancer (CRC) originates from pre-existing polyps in the colon. The development of different subtypes of CRC is influenced by various genetic and epigenetic characteristics. CpG island methylator phenotype (CIMP) is found in about 15-20% of sporadic CRCs and is associated with hypermethylation of certain gene promoters. This study aims to find prognostic genes and compare their expression and methylation status as potential biomarkers in patients with serrated sessile adenomas/polyps (SSAP) and CRC, in order to evaluate which, one is a better predictor of disease.

METHOD

This study employed a multi-phase approach to investigate genes associated with CRC and SSAP. Initially, two gene expression datasets were analyzed using R and Limma package to identify differentially expressed genes (DEGs). Venn diagram analysis further refined the selection, revealing four genes from the Weissenberg panel with significant changes. These genes, underwent thorough in silico evaluations. Once confirmed, they proceeded to wet lab experimentation, focusing on expression and methylation status. This comprehensive methodology ensured a robust examination of the genes involved in CRC and SSAP.

RESULT

This study identified cancer-specific genes, with 8,351 and 1,769 genes specifically down-regulated in SSAP and CRC tissues, respectively. The down-regulated genes were associated with cell adhesion, negative regulation of cell proliferation, and drug response. Four highly downregulated genes in the Weissenberg panel, including CACNA1G, IGF2, MLH1, and SOCS1. In vitro analysis showed that they are hypermethylated in both SSAP and CRC samples while their expressions decreased only in CRC samples.

CONCLUSION

This suggests that the decrease in gene expression could help determine whether a polyp will become cancerous. Using both methylation status and gene expression status of genes in the Weissenberg panel in prognostic tests may lead to better prognoses for patients.

Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Value of ctDNA methylation biomarkers in diagnosis of colorectal tumors

Tweetable abstract DNA methylation alterations have been identified as promising biological markers for early-stage colorectal cancer detection. Here, the authors highlight some recent advances in DNA methylation and its role in the early diagnosis and overall disease course management of colorectal tumors. New insights into DNA methylation biomarkers for colorectal cancer early diagnosis and management are discussed.

A Multi-Omics Overview of Colorectal Cancer to Address Mechanisms of Disease, Metastasis, Patient Disparities and Outcomes

Human colorectal cancer (CRC) is one of the most common malignancies in men and women across the globe, albeit CRC incidence and mortality shows a substantial racial and ethnic disparity, with the highest burden in African American patients. Even with effective screening tools such as colonoscopy and diagnostic detection assays, CRC remains a substantial health burden. In addition, primary tumors located in the proximal (right) or distal (left) sides of the colorectum have been shown to be unique tumor types that require unique treatment schema. Distal metastases in the liver and other organ systems are the major causes of mortality in CRC patients. Characterizing genomic, epigenomic, transcriptomic and proteomic (multi-omics) alterations has led to a better understanding of primary tumor biology, resulting in targeted therapeutic advancements. In this regard, molecular-based CRC subgroups have been developed that show correlations with patient outcomes. Molecular characterization of CRC metastases has highlighted similarities and differences between metastases and primary tumors; however, our understanding as to how to improve patient outcomes based on metastasis biology is lagging and remains a major obstacle to improving CRC patient outcomes. In this review, we will summarize the multi-omics features of primary CRC tumors and their metastases across racial and ethnic groups, the differences in proximal and distal tumor biology, molecular-based CRC subgroups, treatment strategies and challenges for improving patient outcomes.

Transcriptomes of the tumor-adjacent normal tissues are more informative than tumors in predicting recurrence in colorectal cancer patients

BACKGROUND

Previous investigations of transcriptomic signatures of cancer patient survival and post-therapy relapse have focused on tumor tissue. In contrast, here we show that in colorectal cancer (CRC) transcriptomes derived from normal tissues adjacent to tumors (NATs) are better predictors of relapse.

RESULTS

Using the transcriptomes of paired tumor and NAT specimens from 80 Korean CRC patients retrospectively determined to be in recurrence or nonrecurrence states, we found that, when comparing recurrent with nonrecurrent samples, NATs exhibit a greater number of differentially expressed genes (DEGs) than tumors. Training two prognostic elastic net-based machine learning models-NAT-based and tumor-based in our Samsung Medical Center (SMC) cohort, we found that NAT-based model performed better in predicting the survival when the model was applied to the tumor-derived transcriptomes of an independent cohort of 450 COAD patients in TCGA. Furthermore, compositions of tumor-infiltrating immune cells in NATs were found to have better prognostic capability than in tumors. We also confirmed through Cox regression analysis that in both SMC-CRC as well as in TCGA-COAD cohorts, a greater proportion of genes exhibited significant hazard ratio when NAT-derived transcriptome was used compared to when tumor-derived transcriptome was used.

CONCLUSIONS

Taken together, our results strongly suggest that NAT-derived transcriptomes and immune cell composition of CRC are better predictors of patient survival and tumor recurrence than the primary tumor.

Clinicopathological differences of high Fusobacterium nucleatum levels in colorectal cancer: A review and meta-analysis

Objective

To systematically evaluate the significance of Fusobacterium nucleatum (Fn) levels the clinicopathological impacts of cancer.

Methods

Literature from Pubmed, Embase, and Web of Science was retrieved to collect all English literatures on the correlation between Fn and cancer, and the quality of literatures collected was assessed based on the Newcastle-Ottawa Quality Assessment Scale. The heterogeneity and sensitivity were detected by Stata 14.0 software, and the correlation between Fn and cancer clinicopathological as the effect variables was assessed according to the odds ratio (OR) and 95% confidence interval (CI). The forest plot was drawn.

Results

A total of 19 articles meeting the inclusion criteria were selected. The incidence of Fn prevalence varied considerably (range: 6.1 to 83.3%) and was greater than 10% in 13 of 19 studies. Compared with those with no/low Fn levels, the high levels of Fn was positively associated with vascular invasion, nerve invasion, depth of invasion, and distant metastasis [vascular invasion: OR = 1.66, 95%CI(1.07, 2.57), I² = 21.9%, fixed effect model; nerve invasion: OR = 1.36, 95%CI(1.00, 1.84), I² = 43.1%, fixed effect model; infiltration depth: OR = 1.94, 95%CI(1.20, 3.15), I² = 67.2%, random effect model; distant metastasis: OR = 1.80, 95%CI(1.23, 2.64), I² = 3.4%, fixed effect model]. Patients with MLH1 methylation always present a higher Fn levels than those without methylation [OR = 2.53, 95%CI(1.42, 4.53), P = 0.01, I² = 57.5%, random effect model]. Further, Fn was associatedwith the molecular characteristics of cancers [MSI-H Vs. MSS/MSI-low: OR = 2.92, 95%CI(1.61, 5.32), P = 0.01, I² = 63.2%, random effect model; High Vs. Low/Negative CIMP: OR = 2.23, 95%CI(1.64, 3.03), P = 0.01, I² = 64.2%, random effect model; KRAS mutation Vs. wild-type: OR = 1.24, 95%CI(1.04, 1.48), P = 0.02, I² = 27.0%, fixed effect model; Present Vs. Abscent BRAF mutations: OR = 1.88, 95%CI(1.44, 2.45), P = 0.01, I² = 24.2%, fixed effect model]. The cancer patients with high levels of Fn often have worse RFS than those with no/low Fn levels[OR = 1.14, 95%CI(0.61, 1.68), P = 0.01, I² = 80.7%, random effect model].

Conclusion

This review and meta-analysis showed that Fn could be used to predict unfavorable prognosis and function as potential prognostic biomarkers in colorectal cancer (CRC). Our data may have implications for targeting Fn to develop strategies for cancer prevention and treatment.

Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients

Genome-wide analysis of cell-free DNA methylation profile is a promising approach for sensitive and specific detection of many cancers. However, scaling such assays for clinical translation is impractical because of the high cost of whole-genome bisulfite sequencing. We show that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors most of the cancer-specific methylation signature. Here, we report on the simple and effective heat enrichment of CpG-rich regions for bisulfite sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation and quantitative tracking of colorectal cancer patient's response to treatment at much reduced sequencing cost suitable for frequent monitoring. We also show tumor epigenetic subtyping using Heatrich-BS, which could enable patient stratification. Heatrich-BS holds great potential for highly scalable screening and monitoring of cancer using liquid biopsy.

Emerging roles of cystathionine β-synthase in various forms of cancer

The expression of the reverse transsulfuration enzyme cystathionine-β-synthase (CBS) is markedly increased in many forms of cancer, including colorectal, ovarian, lung, breast and kidney, while in other cancers (liver cancer and glioma) it becomes downregulated. According to the clinical database data in high-CBS-expressor cancers (e.g. colon or ovarian cancer), high CBS expression typically predicts lower survival, while in the low-CBS-expressor cancers (e.g. liver cancer), low CBS expression is associated with lower survival. In the high-CBS expressing tumor cells, CBS, and its product hydrogen sulfide (H₂S) serves as a bioenergetic, proliferative, cytoprotective and stemness factor; it also supports angiogenesis and epithelial-to-mesenchymal transition in the cancer microenvironment. The current article reviews the various tumor-cell-supporting roles of the CBS/H₂S axis in high-CBS expressor cancers and overviews the anticancer effects of CBS silencing and pharmacological CBS inhibition in various cancer models in vitro and in vivo; it also outlines potential approaches for biomarker identification, to support future targeted cancer therapies based on pharmacological CBS inhibition.

CpG Island Methylator Phenotype-A Hope for the Future or a Road to Nowhere?

The CpG island methylator phenotype (CIMP) can be regarded as the most notable emanation of epigenetic instability in cancer. Since its discovery in the late 1990s, CIMP has been extensively studied, mainly in colorectal cancers (CRC) and gliomas. Consequently, knowledge on molecular and pathological characteristics of CIMP in CRC and other tumour types has rapidly expanded. Concordant and widespread hypermethylation of multiple CpG islands observed in CIMP in multiple cancers raised hopes for future epigenetically based diagnostics and treatments of solid tumours. However, studies on CIMP in solid tumours were hampered by a lack of generalisability and reproducibility of epigenetic markers. Moreover, CIMP was not a satisfactory marker in predicting clinical outcomes. The idea of targeting epigenetic abnormalities such as CIMP for cancer therapy has not been implemented for solid tumours, either. Twenty-one years after its discovery, we aim to cover both the fundamental and new aspects of CIMP and its future application as a diagnostic marker and target in anticancer therapies.

HOGG1-assisted DNA methylation analysis via a sensitive lanthanide labelling strategy

The assessment of DNA methylation level is an important indicator for the diagnosis and treatment of some diseases. DNA methylation assays are usually based on nucleic acid amplification strategies, which are time-consuming and complicated in operation procedures. Herein, we proposed a sensitive lanthanide-labelled ICP-MS method for DNA methylation analysis that exploited the feature of Human 8-oxoGuanine DNA Glycosylase (hOGG1), which specifically recognizes 8-oxo-G/5mC base pairs to effectively distinguish methylated DNA. A low limit of detection of 84 pM was achieved, and a 0.1% methylation level can be discriminated in the mixture, without any amplification procedure. Compared with commonly used nucleic acid amplification strategies, this proposed method is time-saving and low probability of false positive. Moreover, this work has been successfully validated in human serum samples, the recovery rates is between 96.7% and 105%, and the relative standard deviation (RSD) is in the range of 3.0%-3.5%, indicating that this method has the potential to be applied in clinical and biological samples quantitative analysis.