Blood test

The early detection of cancer has been proven to significantly improve patient survival rates and quality of life, as well as reduces the cost and complexity of cancer treatment. Therefore, the discovery and development of novel biomarkers are in critical need for the screening and surveillance of high-risk populations to enable prompt and successful treatment. Although traditional biopsies have been an integral part of cancer care for decades, biopsies are invasive, may induce complications and depend on the tumor location are not always feasible to access.

In this context, a liquid biopsy is less burdensome than a tissue biopsy and offers simple, fast and cost-efficient monitoring of disease status or response to treatment. [1][2] Moreover, tissue biopsies may not correctly reflect the complex molecular profile of a primary tumor because of its intratumoral variations or spatial heterogeneity which can only be addressed by sampling biopsies from different tumor areas. [3] In contrast, liquid biopsies can offer a more comprehensive cross-sectional information of heterogeneous diseases. [4] Indeed, due to the increasing knowledge of the pathways causing cancer and instrumental developments, liquid biopsy has begun to attract interest in implementation for clinical practice and routine molecular diagnostics.

Image 1.0 Scientists have discovered that dying tumor cells release small pieces of their DNA into the bloodstream. These pieces are called cell-free circulating tumor DNA (ctDNA). This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

A Multimodal Platform: Source of Genomic, Epigenomic and Proteomic Information
In recent years, several cancer-derived components that circulate in our body fluids, [5] such as circulating tumor cells (CTCs),[6][7] circulating cell-free nucleic acids (RNA and DNA),[8][9][10] extracellular vesicles (EVs)/exosomes, [11][12][13] and proteins [14] have been extensively investigated for cancer research. Isolation and molecular analysis of these tumor-derived components including genomic, epigenomic and proteomic assessments from liquid biopsy samples represent a new multimodal diagnostic tool. In particular, circulating cell-free DNA (cfDNA) has emerged as a potential biomarker and is being investigated to distinguish between signals from non-cancer and pre-cancerous populations in translational and clinical research. [15]

A fraction of the total cfDNA in the body fluids called circulating tumor DNA (ctDNA) is derived from tumor cells primarily undergoing apoptosis or necrosis and it has been mostly used to monitor the response to therapy and to assess the development of therapy guidance. [16] The cobas® EGFR Mutation Test v2 (Roche Diagnostics) is the first Food and Drug Administration (FDA-) approved test for the detection of the epidermal growth factor receptor (EGFR) gene, in DNA derived from plasma samples, as a companion diagnostic for the non-small cell lung cancer (NSCLC) therapy. An increasing number of studies demonstrate the potential use of ctDNA as a surrogate marker for multiple indications in various cancer types, including diagnosis, prognosis, and monitoring.

Although the detection of point mutations within ctDNA has a great potential to locate known druggable mutations and impact therapy decisions, this mutation-based approach has less sensitivity for early detection of cancer. Furthermore, due to the limited number of recurrent mutations available for discriminating ctDNA from total cfDNA; a large proportion of the genetic changes identified in a potentially relevant gene are not clinically interpretable and those variants are clinically less significant.

Illustration 2.0. Cancer screening is, in most cases inconvenient and invasive. However, in the prevention of cancer, screening is critical. Cancer patients have a 90% chance of survival if cancer is detected at stage I versus only a 5% chance at stage IV. To improve cancer screening, researchers at Laboratory for Advanced Medicine (LAM) have liquid biopsy tests, using a simple blood draw, that combines artificial intelligence (AI) and machine learning to identify unique and proprietary DNA signatures that predict the presence of cancer as early as stage I. Illustration courtesy: Laboratory for Advanced Medicine

DNA Methylation Classifiers in Circulating Cell-Free DNA
It has been well documented that cancer is not an exclusively genetic disease, but its progression is highly dependent on additional biological processes such as immune activity, tissue microenvironment, and epigenetics. Among them, epigenetic alterations such as abnormal patterns of DNA methylation, histone post-translational modifications and changes in chromatin composition, have led to new opportunities for cancer care. Researchers have emphasized that epigenetic abnormalities might play an influential role in the earliest steps of cancer initiation and the progression of malignancies.

Epigenetic variants involve a change in the DNA methylation pattern within a gene’s CpG islands that leads to the silencing of tumor suppressor genes and subsequent oncogenesis. Unlike genetic alterations, epigenetic variants have a high potential and wide scope to be implemented as early diagnosis biomarkers due to their involvement in the initiation of carcinogenic pathways [17][18]. Both global hypomethylation and hypermethylation at selected CpG islands have revealed the potential of DNA methylation for non-invasive detection and monitoring of various cancer types [19].

In particular, the alterations in the methylation status that often occur in the promoter regions of specific transcription factors are among the most frequent molecular changes that are associated with early molecular events in carcinogenesis and thus show great promise as biomarkers for the early stage of various cancer types [20].

In addition, aberrant methylation of CpG sites within tumor suppressor genes (TSGs) has been shown to correlate with clinically relevant information and has the potential to be used for cancer diagnosis and identification of the cancer tissue of origin. [21] Although the mechanisms underlying cancer development are complicated and carcinogenesis is a multistep process that results from the accumulation of genetic and epigenetic alterations, several investigations showed that detection of DNA methylation patterns of aberrantly methylated CpG sites may provide higher sensitivity over detecting single or few mutation variants.

The Impact of DNA Methylation for Cancer Detection and Clinical Utility
Recent epigenetic biomarker discovery and validation are making well-established epigenetic modifications a promising target as biomarkers for the early detection of cancer and the prediction of clinical outcomes and patient monitoring. Among all studied epigenetic biomarkers DNA methylation is the most frequently examined in various cancers [22] and has been recognized to be most useful for sensitive detection of disease which resulted in an improved clinical outcome for various types of cancer.

The last decades witnessed an exponential development in the analysis of DNA methylation and several techniques have been utilized for cancer diagnostics with high sensitivity, specificity, and accurate detection capacity.

The analysis of ctDNA methylation from bodily fluids, such as blood, saliva or urine, could also be very useful for risk assessment and monitoring of disease progression. In particular, both plasma-derived and serum-derived cfDNA/ctDNA have now been widely evaluated as novel biomarkers for liquid biopsy in cancer diagnosis, prognosis and as surrogates for DNA methylation profiling in various cancer types [23][24]. The methylation markers have been used for disease stratification and also been reported to be of prognostic significance.

DNA Methylation Techniques and Representative Biomarkers
Numerous methods can be applied for the detection of DNA methylation biomarkers, either at a genome-wide scale or a locus-specific level. Mainly, three principal approaches are exploited for the detection or isolation of DNA methylation, namely immunoprecipitation, methyl-sensitive restriction enzymes, and sodium bisulfite conversion. The different techniques that have been developed to detect DNA methylation have their advantages and limitations.

Emerging studies have already revealed useful diagnostic and prognostic DNA methylation markers on multiple tumor genes for various cancer types [25]. For example, GSTP1, RASSF1A, and RARB2 for breast cancer; CDKN2A, ARF, MGMT, and GSTP1 for bladder cancer; FBN2, TAC1 and SEPT9 for colorectal cancer; RASSF1A, PRDM1, DAPK1 and 3OST2 for lung cancer; GSTP1, RASSF1, and RARB for prostate cancer, have been evaluated for their potential as noninvasive epigenetic markers in the body fluids of cancer patients.[26]

Efforts toward the development of methylation-based early detection of tumors are well underway in research laboratories worldwide and several technologies have been evolving rapidly that can be directly applied for DNA methylation biomarkers discovery and validation. Two tests have progressed through to FDA PMA approval, the blood-based Epi proColon® (Epigenomics) and the stool-based Cologuard® (Exact Sciences) and several other liquid biopsy platforms received breakthrough device designations from the FDA, suggesting that others may soon join this niche. In addition, several companies have developed blood tests for the early detection of multiple cancer types by using methylation-based analysis. For example, Laboratory for Advanced Medicine is focused on cancer-specific DNA methylation and also received FDA’s breakthrough designation for its IvyGene Liver Dx for early detection of liver cancer.

Laboratory for Advanced Medicine has been analyzing methylation for years, while many other companies have only just recently identified methylation analysis as the key for early cancer detection and differentiation. DNA methylation technology preferentially targets the most informative regions of the genome and uses machine-learning algorithms to both detect the presence of cancer and identify the tumor’s tissue of origin when cancer is present. The continued technological development and increasing commercialization activity in the DNA-methylation based diagnostics sector are leading to a fast-paced, innovative, and competitive environment that will result in significant benefits to patients for the early detection and management of cancer [27].

Artificial Intelligence (AI) and Machine Learning (ML) to De-code Methylation Patterns in Cancer
The development of a successful biomarker requires specific thresholds for test performance and precise clinical utility. Implementation of AI and ML algorithms advance the analysis of large amounts of high-dimensional biological and medical data that could help to de-code weak signals in the liquid biopsy markers at an early stage of cancer. There have been several approaches using AI and ML in epigenetics research including epigenome mapping and mining of complex data to derive biological insights from the existing “big data” to understand the mechanisms of disease and improve diagnostic tests for clinical applications.

Over the years, companies like Laboratory for Advanced Medicine, Freenome, Grail and Exact Sciences have been implementing AI and ML algorithms and used the power of data science to identify and validate cancer-specific DNA methylation markers. Moreover, applications of AI and ML are already playing an important role in liquid biopsy-based cancer care and significantly speeding up the process of analyzing a vast amount of data to provide faster and better-advised decision-making. [28]

Conclusions and Future Perspectives
As liquid biopsy options grow, the evolving field will bring diagnostic solutions for early detection that goes beyond the utilities of tissue biopsy for cancer care and management. With the high-throughput DNA methylation detection approaches and the continued reduction in the cost of Next-Generation Sequencing (NGS), the use of whole methylomes for biomarker discovery is becoming more common.

Given the greater consistency of DNA methylation changes in cancer compared to mutations, methylation is a promising target for the development of biomarkers for early detection. Recent advances and significant ongoing research in the implementation of epigenetics for early cancer diagnostics have provided novel means for including DNA-methylation analysis to the arsenal of the liquid biopsy approach.

Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques are essential before considering a liquid biopsy for daily practice as an early diagnostic tool, or possibly as a companion diagnostic test for precision medicine. The DNA-methylation based approach is confirmed to be sensitive and specific enough to detect cancers at an early stage, therefore ctDNA methylation does provide a possible alternative for cancer diagnosis and surveillance for routine clinical applications in the future.

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