Genome-wide discovery of circulating cell-free DNA methylation biomarkers for colorectal cancer detection

Quantification method of ctDNA using cell-free DNA methylation profile for noninvasive screening and monitoring of colon cancer

BACKGROUND

Colon cancer ranks as the second most lethal form of cancer globally. In recent years, there has been active investigation into using the methylation profile of circulating tumor DNA (ctDNA), derived from blood, as a promising indicator for diagnosing and monitoring colon cancer.

RESULTS

We propose a liquid biopsy-based epigenetic method developed by utilizing 49 patients and 260 healthy controls methylation profile data to screen and monitor colon cancer. Our method initially identified 901 colon cancer-specific hypermethylated (CaSH) regions in the tissues of the 49 cancer patients. We then used these CaSH regions to accurately quantify the amount of circulating tumor DNA (ctDNA) in the blood samples of these same patients, utilizing cell-free DNA methylation profiles. Notably, the methylation profiles of ctDNA in the blood exhibited high sensitivity (82%) and specificity (93%) in distinguishing patients with colon cancer from the control group, with an area under the curve of 0.903. Furthermore, we confirm that our method for ctDNA quantification is effective for monitoring cancer patients and can serve as a valuable tool for postoperative prognosis.

CONCLUSIONS

This study demonstrated a successful application of the quantification of ctDNA among cfDNA using the original cancer tissue-derived CaSH region for screening and monitoring colon cancer.

Tissue informative cell-free DNA methylation sites in amyotrophic lateral sclerosis

Cell-free DNA (cfDNA) is increasingly recognized as a promising biomarker candidate for disease monitoring. However, its utility in neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS), remains underexplored. Existing biomarker discovery approaches are tailored to a specific disease context or are too expensive to be clinically practical. Here, we address these challenges through a new approach combining advances in molecular and computational technologies. First, we develop statistical tools to select tissue-informative DNA methylation sites relevant to a disease process of interest. We then employ a capture protocol to select these sites and perform targeted methylation sequencing. Multi-modal information about the DNA methylation patterns are then utilized in machine learning algorithms trained to predict disease status and disease progression. We applied our method to two independent cohorts of ALS patients and controls (n=192). Overall, we found that the targeted sites accurately predicted ALS status and replicated between cohorts. Additionally, we identified epigenetic features associated with ALS phenotypes, including disease severity. These findings highlight the potential of cfDNA as a non-invasive biomarker for ALS.

Circulating Nucleic Acids in Colorectal Cancer: Diagnostic and Prognostic Value

Colorectal cancer (CRC) is the third most prevalent cancer in the world and the fourth leading cause of cancer-related mortality. DNA (cfDNA/ctDNA) and RNA (cfRNA/ctRNA) in the blood are promising noninvasive biomarkers for molecular profiling, screening, diagnosis, treatment management, and prognosis of CRC. Technological advancements that enable precise detection of both genetic and epigenetic abnormalities, even in minute quantities in circulation, can overcome some of these challenges. This review focuses on testing for circulating nucleic acids in the circulation as a noninvasive method for CRC detection, monitoring, detection of minimal residual disease, and patient management. In addition, the benefits and drawbacks of various diagnostic techniques and associated bioinformatics tools have been detailed.

Association between heat shock factor protein 4 methylation and colorectal cancer risk and potential molecular mechanisms: A bioinformatics study

BACKGROUND

We previously demonstrated that heat shock factor protein 4 (HSF4) facilitates colorectal cancer (CRC) progression. DNA methylation, a major modifier of gene expression and stability, is involved in CRC development and outcome.

AIM

To investigate the correlation between HSF4 methylation and CRC risk, and to uncover the underlying molecular mechanisms.

METHODS

Differences in β values of HSF4 methylation loci in multiple malignancies and their correlation with HSF4 mRNA expression were analyzed based on Shiny Methylation Analysis Resource Tool. HSF4 methylation-related genes were identified by LinkedOmics in CRC, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Protein-protein interaction network of HSF4 methylation-related genes was constructed by String database and MCODE algorithm.

RESULTS

A total of 19 CpG methylation loci were identified in HSF4, and their β values were significantly increased in CRC tissues and exhibited a positive correlation with HSF4 mRNA expression. Unfortunately, the prognostic and diagnostic performance of these CpG loci in CRC patients was mediocre. In CRC, there were 1694 HSF4 methylation-related genes; 1468 of which displayed positive and 226 negative associations, and they were involved in regulating phenotypes such as immune, inflammatory, and metabolic reprogramming. EGFR, RELA, STAT3, FCGR3A, POLR2K, and AXIN1 are hub genes among the HSF4 methylation-related genes.

CONCLUSION

HSF4 is highly methylated in CRC, but there is no significant correlation between it and the prognosis and diagnosis of CRC. HSF4 methylation may serve as one of the ways in which HSF4 mediates the CRC process.

eDAVE - Extension of GDC data analysis, visualization, and exploration tools

Publicly available repositories such as Genomic Data Commons or Gene Expression Omnibus are a valuable research resource useful for hypothesis driven research as well as validation of the results of new experiments. Frequently however, the use of those opulent resources is challenging because advanced computational skills are required to mine deposited data. To address this challenge, we have developed eDAVE, a user-friendly, web and desktop interface enabling intuitive and robust analysis of almost 12 000 methylomes and transcriptomes from over 200 types of cells and tissues deposited in the Genomic Data Commons repository. The application is implemented in Python, supported for major browsers and available at: https://edave.pum.edu.pl/.

New Advances in Gastroenterology: The Crucial Role of Molecular Medicine

The significant progress we have recently observed in the field of gastroenterology, both in the understanding of pathophysiological mechanisms and in the diagnosis and treatment of diseases, is closely related to the improvement and discovery of new biomolecular techniques [...].

Comparing the advantages, disadvantages and diagnostic power of different non-invasive pre-implantation genetic testing: A literature review

To improve embryo transfer success and increase the chances of live birth in assisted reproductive methods, there is a growing demand for the use of pre-implantation genetic testing (PGT). However, the invasive approaches used in PGT have led to in vitrofertilization failure and abortions, increasing anxiety levels for parents. To address this, non-invasive PGT methods have been introduced, such as the detection of DNA in blastocoel fluid of blastocysts and spent culture media (SCM). These methods have proven to be minimally invasive and effective in detecting aneuploidy in the chromosomes of human embryos. This review aims to explore the different approaches to pre-implantation diagnosis, including invasive and non-invasive methods, with a particular focus on non-invasive PGT (niPGT). The search strategy involved gathering data from scientific databases such as PubMed, Google Scholar, and Science Direct using relevant keywords. The search was conducted until January 2023. In total, 22 studies have successfully reported the detection and amplification of cell-free DNA in the embryonic SCM. It is important to note that niPGT has some limitations, which include differences in indicators such as cell-free DNA amplification rate, concordance, level of maternal DNA contamination, sensitivity, and specificity between SCM samples and biopsied cells. Therefore, more extensive and detailed research is needed to fully understand niPGT's potential for clinical applications.