Cancer is a leading cause of death globally which needs appropriate diagnosis methods. “Solid biopsies” cannot always be performed since it has invasive characteristic and cannot reflect current tumor dynamics or sensitivity to the treatment. Therefore, it is of great value to develop noninvasive detecting methods that could monitor the real-time dynamics of cancer. “Liquid biopsy” of circulating nucleotide acids [circulating tumor DNA (ctDNA), circulating RNA or microRNAs, etc.] may be an ideal one for patients with cancer (1). This review aims at describing the current contribution of ctDNA detection in cancer patients and to analyze the advantages and disadvantages.
Cancer cells often rely on the activation of dominant oncogenes for proliferation and survival. The presence of specific gene alteration can have diagnostic value, reflect patient’s responsiveness to the treatments and predict survival (2). Tumor DNA can be detected by tracking tumor-specific mutations or aberrant rearrangements. Since multi-site biopsies repeated sequentially is unpractical, a non-invasive DNA detection approach from peripheral blood may help reflecting dynamic changes in cancer cells. At present, advanced technologies have turned precise ctDNA mutation detection to reality (3).
Genetic mutation in cancer and genome-wide association analysis
Genetic mutation profiles
Variety types of cancer are sensitive to inhibition of a certain kind of molecular pathway signaling. Somatic mutations and epigenetic alterations in known components of the signaling network might influence treatment efficacy. Moving beyond the target gene, tumor cells can develop therapy resistance through acquisition of mutations (4). Therefore, additional pathway signatures might be involved in prediction of individual response.
Multigene test moved the clinical pharmacogenomics tests away from conventional sequencing of single genes and marked a huge step towards more comprehensive analysis of cancer genome ever since. It allows the oncologists to identify the targetable genetic aberrations and direct the patients to the targeted therapy if a potential drug is available (5,6). However, cancer is a multigene disease which arises as a result of the mutational activation of oncogenes coupled with the mutational inactivation of tumor suppressor genes. These genetic alterations can synergize or antagonize each other and often occur according to a preferred sequence.
Molecular cytogenetic expectation
The methods of molecular cytogenetic, such as spectral karyotyping, fluorescence in situ hybridization (FISH) and chromosome-based comparative genomic hybridization (CGH) improved resolution and genome coverage compared with conventional karyotyping based on the visualization of metaphase chromosomes. However, the most substantial developments in obtaining increasingly more detailed and comprehensive characterizations of tumor genomes have been described during the last decade. The emergence of a range of new technologies including “omics” profiling, microarray-based CGH and single nucleotide polymorphism (SNP) analysis, and next-generation sequencing (NGS) enabled to interrogate the tumor genome and proteome in a more unbiased way and led to remarkable insight into tumor biology (7).
Genome-wide scan using microarray platform are applied to identify genetic variants, including Array-based CGH, which is one of the approaches to improve the detection of structural variation affecting many base pairs. This technique is based on the principle of complementary hybridization between the array of oligonucleotide probes immobilized on a slide and two differentially fluorescently labeled test and reference DNA samples (8). The principles of SNP array are similar and based on the hybridization of fragmented single-stranded DNA to arrays containing unique nucleotide probe sequences immobilized on solid surface (9). The specialized equipment can measure the signal intensity associated with each probe and its target after hybridization. SNP array platforms contain oligonucleotide probes that interrogate both copy number and SNP sites. Genome-wide association studies (GWAS) became possible by the availability of chip-based microarray technologies for analysis of more than one million SNP (10,11).
Mutation detection using cutting-edge technologies
Targeted plasma re-sequencing (TAm-Seq)
Forshew et al. reported that de novo mutation can be detected through TAm-Seq noninvasively in 2012, which they termed as TAm-Seq (12). It allowed the re-sequencing of approximately 6,000 nucleotides whilst maintaining high depth analysis. The authors conducted a proof-of-concept experiment by tracking ctDNA from an ovarian patient, which had been re-sequenced tumor tissue from a right oophorectomy specimen and identified a TP53 mutation. TAm-Seq analysis revealed the emergence of an EGFR mutation in plasma samples, as the cancer progressed, which was not found in the original specimen. Further investigation identified low frequencies of EGFR mutation from initial samples. Forshew et al. hypothesized that as chemotherapy regimens restrained the growth of other clones, the resistant EGFR clone, which was initially present only at low frequency, gained in dominance. They demonstrate that plasma analysis can identify heterogeneous clones from different sites of the body.
Massively paralleled sequencing (MPS)
Personalized analysis of rearranged ends (PARE) was developed by Leary et al. to detect unselected genetic events that span across the whole genome (13). Similarly, another MPS named “Shotgun” was used by Chan et al. in 2013 (14). They identified copy number variations and single nucleotide variants (SNVs) of the whole genome from the plasma of 4 patients with hepatocellular carcinoma (HCC). Furthermore, they demonstrated the ability of MPS to track ctDNA level changes pre- and post-surgery. Interestingly, shotgun MPS of the plasma was also able to distinguish between tumor types in a patient with synchronous breast and ovarian tumors. The above studies illustrate that ctDNA analysis, through de novo mutation detection, can continue to track disease burden as tumors evolve, without the need for re-biopsy.
Whole-genome sequencing (WGS)
WGS enables detecting ctDNA in patients prohibitively expensive, regarding the limit analysis of whole genome MPS to a small number of samples due to expense (15). Although low depth, and therefore reduced cost, WGS approaches have been successful at detecting copy number variations, a higher depth of coverage is often required to detect rearrangements at high resolution or SNVs directly from plasma DNA. Furthermore, where low mutant: wild type allele frequencies exist, e.g., in early stage disease, an even higher depth of coverage would be necessary to detect ctDNA fragments. In addition, WGS approaches detect a higher ratio of intronic or passenger mutations than targeted re-sequencing (16). The clinical significance of passenger mutations is currently unknown and often not targetable.
Whole exome sequencing (WES)
To make routine analysis of de novo mutations in serial plasma samples possible, WES was performed to track tumor evolution in response to therapy. Murtaza et al. used this approach in a proof-of-concept study involving 6 patients with metastatic tumors. Plasma samples were collected at the beginning of treatment and at the time of relapse. Subsequent re-sequencing and variant analysis revealed that by comparing the relative representation of mutations in pre- and post-relapse samples, one could identify enrichment of mutations that may drive resistance WGS can screen a larger spectrum of the genome but is currently too expensive for routine use to detect SNVs, whereas WES approaches allow more in-depth interrogation of multiple regions but is less sensitive to identifying copy number changes (17). This work demonstrated a much more cost effective way for mutation sequencing.
Tumor-specific gene mutations
Pancreatic cancer has the distinction of being the first solid tumor associated with a specific mutation in ctDNA. This is partly because the KRAS gene is frequently mutated and easy to detect. Sorenson et al. used allele-specific amplification to assay for mutations in codon 12 in the plasma or serum of pancreatic adenocarcinoma patients (18).
The sensitivity of detecting primary pancreatic cancer on the basis of ctDNA is mostly 30% to 50% while the specificity is generally higher (approximately 90%) (19). A variety of detection methods including restriction digestion and single-stranded conformational polymorphism have been used. In one study, sensitivity was improved when CA199 was measured in combination with DNA measurements (20). However, although at a lower frequency (5% to 15%) than adenocarcinoma, pancreatitis cases also showed KRAS gene mutilations (21). Most studies have focused on KRAS mutations in pancreatic cancer because of their prevalence, other approaches have been tried. The advents of higher-throughput methods, such as NGS and digital PCR, have had a profound effect on this field. For instance, one recent study using this method showed that pancreatic duct cancer had a high rate of ctDNA than other malignancies, more so in metastatic disease than non-metastatic disease. In summary, for clinical and biological reasons, pancreatic cancer is an ideal candidate for the diagnostic and prognostic use of detection of ctDNA (22).
The overall detection rates of KRAS mutations in serum or plasma of patients with colorectal cancer were 25% to 50% (24). Also, KRAS mutations in ctDNA have been reported to have the highest level in patients with more advanced stage (25). Besides, KRAS mutations in ctDNA are also associated with a higher risk of recurrence after surgery (26,27). Analysis of circulating mutant DNA could also monitor response to monoclonal antibody therapy for colorectal cancer, which makes repeatedly monitoring patients during treatment possible (28).
The exploration for APC mutations in ctDNA has focused on exon 15, which is a hotspot for APC mutations in colorectal cancer. The rate of APC mutation detection in primary ctDNA is approximately 45%. As for TP53, the mutation rate has been identified in ctDNA in about 40% of cases. Most studies focused on portions of TP53 between exons 4 and 8, the most commonly locations of TP53 mutations in colorectal cancer (24).
Unless targeting ctDNA alterations in hotspots of certain genes, a panel targeting mutations of the KRAS, TP53, and APC genes enabled the detection of at least one gene mutation from approximately 75% of colorectal cancer tissue. However, those mutations could only be detected in the serum of 45% of these patients (29).
ctDNA methylation—epigenetic changes
Unless DNA mutation, there is also gene methylation which affects their expression that can be found in ctDNA. Tumorigenesis is regulated not only by genetic but also by epigenetic alterations (2). In fact, as for detection, there are a variety of genes mutated in tumors, even when a gene is consistently mutated in a particular cancer, the gene mutations may be spread over large region that makes evaluation difficult. DNA methylation tends to occur in CpG dinucleotides in the promoter region of tumor suppressor genes that leads to expression silencing (30). Therefore, methylated ctDNA in recent years is becoming an emerging target and shows promising results.
Methylation detection methods
Methods for methylation detection emerge in an endless stream. Generally it is divided into 3 categories: (I) methylation content: high-performance liquid chromatography (HPLC) or high-performance capillary electrophoresis (HPCE); (II) candidate gene: methylation-sensitive restriction endonuclease-PCR/Southern (MSRE-PCR/Southern), bisulphite sequencing, methylation-specific PCR (MS-PCR), MethyLight, etc.; (III) methylation pattern and methylation profiling: restriction landmark genomic scanning (RLGS), amplification of inter-methylated sites (AIMS), Methylated CpG-island amplification (MCA) and so on. The most common method at present studies is usually MS-PCR.
Tumor-specific gene methylation
Methylation of ctDNA has been reported for many years. Detections of ctDNA methylation mostly focused on colorectal cancer, lung cancer, breast cancer, pancreatic cancer as well as some other types of carcinoma. Compared to mutations, the consistency of DNA methylation alterations makes it a potential promising biomarker for diagnosis, staging, monitoring response and predicting survival for cancer patients.
Colorectal cancer is the third most common cancer both in men and in women worldwide (31). An easy and quick screening test is essential for the early diagnosis for colorectal cancer. It is reported that the promoter hypermethylation status of SEPT9 was high associated with the development of colorectal cancer. In PCR-based retrospective trials for SEPT 9 promoter methylation, sensitivity and specificity were 72-90% and 88-90% respectively (32-35). Another research from USA showed that methylated SEPT9 DNA in plasma may help screening out 72% colorectal cancer with a high specificity of 93% (34). Furthermore, SEPT 9 methylation could be found in precancerous lesions of colorectal cancer. Church et al. conducted a large, prospective trial to assess the accuracy of circulating methylated SEPT9 DNA for detecting colorectal cancer in 7,941 patients using a commercially available assay. It showed a disappointing result that sensitivity and specificity were 48.2% and 91.5%, respectively (36). That may because the population they enrolled were not confirmed cancer patients, which differs to other researches.
Other biomarkers such as well-known novel sequences of APC, RASSF1A and E-cadherin (37,38) as well as novel markers in plasma have also been found to correlate with colorectal cancer. A German study showed that Methylation of helicase-like transcription factor (HLTF) and hyperplasic polyposis 1 (HPP1) in serum significantly correlated with tumor size, stage, and metastatic disease, and were also prognostic factors in metastasized colorectal cancer (39).
Besides, methylation status of H3 lysine 9 (H3K9me3) and H4 lysine 20 (H4K20me3), which are hallmarks of pericentric heterochromatin in healthy donors and patients with colorectal cancer was tested and showed weak correlation between cNUCs and histone methyl marks (40).
Breast cancer is the most common cancer in women both in more and less developed regions. Numerous studies were conducted aiming to analyze the methylation status of biomarker genes in breast cancer and assess possible clinical value, mostly using the candidate gene testing. That means a majority of the makers are the well-established genes, such as cyclin D2, RARβ2 (41), ESR1 (42) and so on. Dulaimi et al. have found that at least one hypermethylation of APC, RASSFIA or DAP-kinase could be found in 94% serum samples of all the breast cancer patients (43). Scholars from All India Institute of Medical Sciences have conducted a serious of prospective studies including 100 invasive ductal breast cancer patients. Methylation status of multidrug resistance 1 (MDR1), Stratifin, ERα and PR, DNA repair genes-BRCA1, MGMT and GSTP1 were tested. Significant correlation was found between methylation status of the promoter of the above genes in tumor tissue and paired serum. However, the sensitivity of these genes was not high (MDR1 50%, Stratifin 56%, ERα 55%, PRB 55%, BCRA1 22%, MGMT 26%, GSTP1 22%) (44-46).
Unlike using the candidate genes, methylation detection in 56 genes (MethDet-56) test was conducted to find novel methylated genes and assess the dynamics of methylation so as to monitor treatment (surgery and hormone therapy). Larger study based on these results was encouraged (41).
Lung cancer is the leading cause of cancer-related death partly because the absence of early detection approach (47). Up to now there is no ideal early diagnostic method. Changes in DNA methylation may occur on its early stage. DNA methylation detection is expected to be an essential method in early diagnosis of lung cancer. There are more than 80 hypermethylated genes related to lung cancer such as APC (48,49), RARb (50,51), RASSF1A (52), CDH13 (48,51), SHOX2 (53), SHP-1 (54). Unless early diagnosis, study focused on correlation of methylation and survival of lung cancer patients showed that CHFR methylation status correlated the results of second-line chemotherapy or EGFR TKIs in 179 of 366 patients (55).
Over-all, methylation test on ctDNA is a very encouraging and promising method to diagnose or monitor tumor. As a unique biomarker having the sufficient specificity and sensitivity is not available, a panel of multiple genes could be used.
Other forms of tumor-specific abnormalities
Microsatellite instability (MSI) and loss of heterozygosity (LOH) are another two types of genetic alterations in tumor that lead to misinterpretation. Many studies have shown that these abnormalities could be found in serum samples from patients with HCC (56,57), malignant mucosal melanoma (MMM) (58), glioma (59) and other tumor types. LOH at microsatellite markers in the plasma may also have potential correlation with diagnosis and prognosis of cancer.
“Liquid biopsy”—ctDNA detection has great potential in cancer diagnose, monitoring, predicting survival. Nevertheless, false-positive results exist. The major challenge with analysis of ctDNA is assay sensitivity and specificity. On this account, multigene panel analysis of ctDNA may lead to increased test sensitivity. However, evidence support this assumption is inadequate. Several hurdles still exist such as the lack of consensus in technical approaches of choice, preferable sample type, storage conditions, candidate molecules and suitable detection technique, et al. At the same time, the standardization of all experimental steps of techniques should be emphasized. A gap exists between reality and our hope of this “liquid biopsy”. Consequently, the development of appropriate biomarkers and more accurate detection methods based on ctDNAs could benefit a lot to cancer patients and may as a result improve the clinical outcome in the near future.
This work was supported by Research and Innovation Project for College Graduates of Jiangsu Province (KYLX_0955), a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) (JX10231801), and grants from Key Academic Discipline of Jiangsu Province “Medical Aspects of Specific Environments”.
Conflicts of Interest: The authors have no conflicts of interest to declare.
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