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The detection of specific hypermethylated WIF1 and NPY genes in circulating DNA by crystal digital PCR™ is a powerful new tool for colorectal cancer diagnosis and screening

Abstract

Background

In oncology, liquid biopsy is of major relevance from theranostic point of view. The searching for mutations in circulating tumor DNA (ctDNA) in case of colorectal cancers (CRCs) allows the optimization of patient care. In this context, independent of mutation status biomarkers are required for its detection to confirm the presence of ctDNA in liquid biopsies. Indeed, the hypermethylation of NPY and WIF1 genes appear to be an ideal biomarker for the specific detection of ctDNA in CRCs. The objective of this work is to develop the research of hypermethylation of NPY and WIF1 by Crystal Digital PCR™ for the detection of ctDNA in CRCs.

Methods

Detection of hypermethylated NPY and WIF1 was developed on Cristal digital PCR™. Biological validation was performed from a local cohort of 22 liquid biopsies and 23 tissue samples from patients with CRC. These patients were treated at the University Hospital of Besancon (France).

Results

The local cohort study confirmed that NPY and WIF1 were significantly hypermethylated in tumor tissues compared to adjacent non-tumor tissues (WIF1 p < 0.001; NPY p < 0.001; non-parametric Wilcoxon paired-series test). Histological characteristics, tumor stages or mutation status were not correlated to the methylation profiles. On the other hand, hypermethylation of NPY or WIF1 in liquid biopsy had a 95.5% [95%CI 77–100%] sensitivity and 100% [95%CI 69–100%] specificity.

Conclusion

Using Crystal digital PCR™, this study shows that hypermethylation of NPY and WIF1 are constant specific biomarkers of CRCs regardless of a potential role in carcinogenesis.

Peer Review reports

Introduction

Colorectal cancer (CRC) is the third most common cancer worldwide with more than one million new cases diagnosed every year. The development of new chemotherapies, especially cancer personalized therapies, has improved outcomes of patients with CRC. The effectiveness of targeted therapies is based on mutational profiles of RAS/MAPK pathway genes [1]. These mutations are typically sought at the time of diagnosis from a cancer tissue biopsy. However, in cases of a non-feasible biopsy, this search can be performed on circulating tumor DNA (ctDNA). Liquid biopsy is an increasingly common oncology test for the diagnosis of cancer and follow-up of treatments. The search for ctDNA mutations is mainly used in a theranostics approach, particularly in lung and colorectal cancers [2]. The liquid biopsy is a non-invasive approach and can be repeated over time to perform dynamic monitoring of tumors. Unfortunately, this theranostic approach depends on the fluctuant release of tumoral DNA in the vascular compartment [3].

Next Generation Sequencing (NGS) strategies are now commonly used for the detection of mutations on ctDNA [4]. Advanced quantitative technologies, such as the digital PCR (dPCR), have been developed to increase sensitivity of detection [5]. The dPCR amplifies millions of individual DNA fragments using thousands of water-in-oil droplets. This compartmentalization increases the detection sensitivity, and is especially adapted for mutations present in low concentration. If no mutations are detected in liquid biopsy, discrimination between an unmutated profile and an absence of ctDNA in the plasma sample is not possible. To address this issue, high sensitivity tumor-specific epigenetic biomarkers have been identified to assert presence of ctDNA [6, 7]. DNA methylation is the most studied epigenetic mechanism in this respect [8].

Indeed, the tumor cell epigenome associates global hypomethylation [9, 10] interspersed with hypermethylated specific regions such as promoters of tumor suppressor genes, and correlated with a decreased expression [11]. These modifications happen in tumorigenesis and many studies are looking at these new epigenetic markers [11, 12].

Based on Roperch and al [13]. and Garrigou and al [14]. studies, DNA hypermethylation of NPY (Neuropeptide Y) and WIF1 (Wnt inhibitory factor 1) appears as a specific marker of ctDNA in CRCs. Hypermethylation of NPY and WIF1 is found in 100% of CRCs [13, 14], while the presence of a defined mutation is inconstant in CRCs. For instance, a mutation of KRAS is only found in 40% of CRCs and therefore cannot be used as a biomarker for the presence of CRCs ctDNA. Thus, hypermethylation of NPY and WIF1 appears to be a better biomarker [6].

In the present study, we adapted a droplet-based dPCR protocol previously described [13, 14] in the Naica Crystal Digital PCR system™ (Stilla Technonologies, Villejuif, France) in order to investigate the hypermethylation of the NPY and WIF1 in CRC tissues or ctDNA. The objective is to determine whether the hypermethylation of NPY and WIF1 is a specific biomarker of CRC in liquid biopsy by Crystal Digital PCR™ and could be used for routine diagnosis, recurrence and treatment follow-up.

Materials and methods

Patients

Digital PCR analyses were conducted on 22 blood and 23 tissue samples from patients with CRC treated at the University Hospital of Besancon (France) (Table 1). Before inclusion all patients provided written informed consenting to the use of their clinical, biological and demographic data for research purposes. Samples were preserved in the framework of the “Tumorothèque Régionale de Franche-Comté”. This scientific board has an authority to approve human studies. And blood samples from patients without any oncologic background (considered as control group) were collected at the “Etablissement Français du sang”. These samples were blood donations.

Table 1 Demographic, anatomopathological and biological data of the cohort. Twenty-three colorectal cancer tumor tissues were included and 22 circulating tumor DNA. For 11 of the tumor tissues, non-tumor tissues close to the tumor were analyzed. The anatomopathological and biological results come from analyses carried out as part of patient management

DNA isolation and bisulfite modification

Tumors DNA was extracted from frozen biopsies and FFPE samples. In EDTA collected blood samples were pre-treated to obtain supernatants which were stored at − 80 °C. Circulating cell-free DNA (cfDNA) was extracted from 4 mL to 6 mL of plasma using the QIAamp® Circulating Nucleic Acid kit (Qiagen®, Hilden, Germany) according to the manufacturer’s protocol and resuspended in 50 μL of buffer. The quantity of DNA was mesured by Qubit 2.0 fluorometer (Invitrogen®, Life Technologies) and were obtain between 1 to 240 ng/μL (mean = 22.6 ng/μL).

For all samples, bisulfite treatment was performed to transform unmethylated cytosine into thymidine without changing methylated cytosine, by EZ DNA Methylation kit® (Zymo Research) for DNA concentration of 1 ng/μL.

Mutation status Analysis by NGS, microsatellite phenotype and MLH1 promoter methylation by pyrosequencing were performed as part of patient management. After bisulfite treatment of tumor DNA, 5 μL of the bisulfite-treated DNA solution was analyzed by a pyrosequencing technique according to the PyroMark™ Q24 CpG MLH1 procedure (Qiagen®, Hilden, Germany). The analyzed promoter sequences correspond to the proximal region, − 209 to − 181, relative to the transcription start site of hMLH1 gene.

Development of the digital PCR analysis

An aberrant hypermethylation of NPY and WIF1 genes has been described in CRCs. We developed a (previously described) 2-panel assay targeting these biomarkers previously described on a Naica Crystal Digital PCR system™ (Stilla Technonologies, Villejuif, France). After bisulfite conversion, a volume of 5 μL of DNA extract was assembled in 20 μL PCR mixtures using 1 X PerfeCTa Multiplex qPCR ToughMix (Quanta Biosciences, Gaithersburg, MD, USA), 100 nM Fluorescein, 1 μM each primer, 250 nM each hydrolysis probe. In Table 2, probe and primer sequences were previously designed by Garrigou et al. [14] (Fig. 1). But we developed Crystal digital PCR™ specific conditions by 95 °C for 5 min, followed by 50 cycles of 95 °C for 15 s and 57 °C for 10 s.

Table 2 Probe and primer sequences for NPY and WIF1 genes
Fig. 1
figure1

Genomic environment of the dPCR target associated with WIF1 and NPY. A) WIF1 is located on the reverse strand of the 12th chromosome’s long arm (12q14.3). The 5′ region of WIF1 is covered by a 1 kb wide CpG island that contains 84 CpG. Within this CpG island is the 67 bases wide dPCR target that contains 5 CpG. The target is entirely contained within the 5’UTR of WIF1 and does not overlap the promoter of WIF1 (chr12: 65,121,532-65,121,731) (Encode: EH38E16200601). B) NPY is located on the short arm of the 7th chromosome (7p15.3). The 5′ region of NPY is covered by a 1,6 kb wide CpG island that contains 123 CpG. Within this CpG island is the 96 bases wide dPCR target that contains 11 CpG. It partially overlaps with the 5’UTR of NPY and is entirely contained within the promoter of NPY (chr7: 24,283,952-24,284,290) (Encode: EH2540595). Illustration not to scale for clarity.

Data analysis

The droplet identification and fluorescence measurements in each detection channel were performed using Stilla’s Crystal Miner® software. Spill-over compensation was defined and applied. Gating of positive and negative droplet clusters was performed.

Transcriptional impact of hypermethylation of NPY and WIF1 was evaluated on the TCGA-COAD data. Transcription data were normalized with Deseq2 [15] and gene expression was compared between non-tumor (n = 41) and tumor samples (n = 480) using bilateral Student test.

Statistical analysis

An analysis of the difference in methylation between tumor and healthy tissue was conducted using the non-parametric Wilcoxon test. The difference in methylation between the 2 groups was determined using a non-parametric Mann-Whitney test; the analysis of more than 2 groups was performed using the non-parametric Kruskal-Wallis test. Spearman’s nonparametric test was used for correlation research. Statistical analyses were performed using GraphPad (GraphPad Software Inc., San Diego, CA). An uncertainty of 5% was defined for each of the tests and a p-value < 0.05 was considered statistically significant.

The required numbers of subjects (RNS) per groups were computed with the software R v4.0.2 using the observed means and standard deviations in our cohort and the usual statistical parameters (a significance level of 0.05 and a power of 0.90). Grouping by tumor/non-tumor, tstandard deviations were significantly different, therefore the ANOVA test was used. This estimation shows that an important difference of the positive droplets number between tumor and non-tumor. For the tumoral status (tumor vs non-tumor), the estimated RNS was 10 samples for WIF1 and 16 samples for NPY. Using a Student test for the liquid biopsies analyzes, the RNS were 10 samples for NPY and 9 samples for WIF1.

In our study, 23 tumor tissues and 22 bloods samples were analysed with powerful significativity (p < 0.001).

Results

Detection of NPY and WIF1 methylation by crystal digital PCR™

A digital PCR technique has been developed on the Naica Crystal Digital PCR system™ (Stilla Technonologies, Villejuif, France) for the detection of NPY and WIF1 genes’ methylation.

A limit of blank (LOB) was calculated for the two detection channels allocated to Cyanine 5 and Cyanine 3 for NPY and WIF1 respectively. A total of 12 experiments were performed with unmethylated DNA quantified at 0.2 ng/μL. Garrigou et al. [14] showed that the rate of false positive droplets is independent of the total amount of DNA. The LOB with the confidence level (1-α) was defined as the maximum number of false positive events that are plausible with a 1-α level probability (95% for risk α = 5%). The number of false positive droplets was recorded to targeted channel detection. The LOB was set as one false positive droplet for NPY and five for WIF1 promoters’ methylation.

A dilution test was performed in order to assess the detection sensibility of the technique. Five concentrations of a fully methylated control DNA (EpiTect Qiagen®, Hilden, Germany) at 10% have been tested: 0.5 ng/μL, 0.25 ng/μL, 0.1 ng/μL, 0.05 ng/μL, and 0.01 ng/μL (Fig. 2). For a concentration of 0.05 ng/μL with a percentage of DNA methylated at 10%, the developed technique was able to detect the methylation of the NPY genes (R2 = 0.9715) and WIF1 (R2 = 0.9775). These results show the high sensibility of this method. The difference in the level of detection between the two targets can be explained by the difference in the numbers of CpG analyzed by our technique (Fig. 1). Indeed, the methylation profile of NPY is more restrictive because 11 CpG must be methylated for their detection. The detection of WIF1 applies to a region of five CpG.

Fig. 2
figure2

Detection of the methylation status of NPY and WIF1 according to the concentration of DNA methylated at 10%. The number of positive droplets is expressed according to the five DNA concentrations: 0.5, 0.25, 0.1, 0.05 and 0.01 ng/μL. The correlation coefficients show the high sensitivity of the technique for low concentrations

Validation on local cohort

Characteristics of the patient population

A cohort of 45 patients (22 blood and 23 tissue samples) with CRC was included in the study (Table 1). The average age of patients was 62 years which is similar to the average age of CRC diagnosis [16]. In the first instance, DNA extractions from 11 tumors/non-tumor tissues pairs were included. Three of those pairs derived from frozen tissue samples and 8 from formalin-fixed paraffin-embedded (FFPE) tissue samples. Tumor tissues corresponded to primary tumors biopsies. Anatomopathological data show that all tumors are adenocarcinomas and that almost half of them are located in the left colon (46%). On the 23 CRCs DNA analyzed, 59% show microsatellite instability (MSI), of which 52% present a MLH1 promoter methylation, and almost half (56%) arbor a KRAS (26%) or BRAF (30%) mutation. In parallel, 22 plasma DNA extracts from CRC patients, mostly stage IV (91%), were included and somatic mutation initially detected in tumor DNA was found for half of the ctDNA samples (n = 11, 50%). The plasma of 10 patients was also analyzed as a control group (Mean age: 49 years (min-max: 21-65y), 50% are female) (Supplementary data).

CRC patient tissues detection of NPY and WIF1 DNA methylation

Using Crystal Digital PCR™, the NPY and WIF1 hypermethylation testing was performed on the 23 tumor tissues from CRC patients. Specific hypermethylation of NPY and WIF1 was observed for all samples (100%). A significant correlation was showed between the number of positive droplets for both genes (R2 = 0.56, p = 0.0016, non-parametric Spearman’s test) (Fig. 3). With non-parametric Spearman’s test, the number of positive droplets was also correlated with the concentration of DNA extracted for WIF1 (R2 = 0.436, p = 0.0377) and for NPY (R2 = 0.809, p < 0.0001). For control group, 11 CRC adjacent non-tumor tissues were used.

Fig. 3
figure3

Correlation of NPY and WIF1 gene methylation status in colorectal tumor tissues. (n = 23, R2 = 0.56, p = 0.0016, non-parametric Spearman’s test)

A comparison of the number of positive droplets was performed according to histology (partially or well differentiated adenocarcinoma) and tumor stage (I and II, III or IV). No significant difference was found between the methylation profile and tumor histology (p = 0.6950; for NPY p = 0.6319 for WIF1; non-parametric Kruskal-Wallis test, n = 21) (Fig. 4A). The same absence is observed with the tumor stage (p = 0.2873 for NPY; p = 0.0517 for WIF1; non-parametric Kruskal-Wallis test, n = 22) (Fig. 4B).

Fig. 4
figure4

Comparison of methylation according to histology, tumor stages and mutation status. Comparison of the methylation of WIF1 and NPY genes according to A) the histology of the tumor (ADC-WD or ADC-PD). Non-parametric Mann-Withney test. B) Tumor stage (stage I and II, III or IV). Non-parametric Kruskal-Wallis test. C) The mutated or non-mutated status of the tumor. Non-parametric Mann-Whitney test. D) Tumor tissues compared to the adjacent healthy tissues. Non-parametric Mann-Withney test in paired series. ADC-WD: well-differentiated adenocarcinoma, ADC-PD: partially differentiated adenocarcinoma

The mutation tumor status as well as its microsatellite status (MSS or MSI) has also been compared with methylation profiles. No significant difference was found for mutation status (p = 0.6137 for NPY; p = 0.2034 for WIF1; non-parametric Mann-Whitney test, n = 18) (Fig. 4C) nor for microsatellite status (p = 0.1439 for NPY; p = 0.8860 for WIF1; non-parametric Mann-Whitney test, n = 22). The percentage of MLH1 promoters’ methylation was not correlated with WIF1 and NPY promoters’ methylation (NPY: R2 = 0.07; WIF1: R2 = 0.45, p = 0.0972; p = 0.8124; non-parametric Spaerman’s test, n = 15).

Importantly, significant hypermethylation of both genes was demonstrated in tumor tissues compared to adjacent non-tumor tissues (NPY p = 0.001; WIF1 p = 0.002; non-parametric Wilcoxon paired-series test) (Fig. 4D). The NPY and WIF1 methylation testing was performed on the 11 pairs of tumor/non-tumor tissue adjacent to the tumor. The WIF1 gene mean positive droplet number for tumor and non-tumor tissue were respectively 6776 and 81. The Area Under Curve (AUC) of the Receiver Operating Characteristic (ROC) curve was 0.937 [0.845–1.000] (Supplementary data 2A). For NPY gene, the mean droplet number for tumor and non-tumor tissue were respectively 6021 and 115. The AUC of the ROC curve was 0.979 [0.933–1.000] (Supplementary data 2B). Using the two biomarkers, we obtained an AUC = 1 [1.000–1.000] on our local cohort (Supplementary data 2C).

As shown by multivariate Anova analyzes, the NPY and WIF1 methylation are powerful biomarkers of all types of CRCs independently of mutations, MSI and MLH1 methylation status. Comparing tumor samples and non-tumor colonic tissues, TCGA data were analyzed for WIF1 and NPY transcripts (Fig. 5). The NPY transcripts in CRCs are lower than in non-tumor tissues (Fig. 5A). However, transcriptomic analysis shows overexpression of WIF1 in CRCs (Fig. 5B).

Fig. 5
figure5

Expression of the NPY and WIF1 mRNA in CRCs tissues and non-tumor tissues. The transcriptomic study of the Cancer Genome Atlas (TCGA) allows the analysis of the levels of mRNA encoded by the genes. A) Thus, it is shown that the level of mRNA encoded by the NPY gene is significantly lower in colorectal cancers than in healthy tissues (p < 10− 4). B) On the other hand, the level of mRNA encoded by the WIF1 gene is higher in colorectal cancers than in healthy tissues (p < 10− 4)

CRC patient liquid biopsies detection of WIF1 and NPY DNA methylation

In the cohort of 22 total circulating DNA samples, hypermethylation of NPY or WIF1 in liquid biopsy had 95.5% of sensitivity [95% CI, 77 to 100%] and 100% of specificity [95% CI, 69 to 100%]. And hypermethylation of NPY or WIF1 was observed for 95.5% of the extracts, of which 77.3% with methylation for both genes. All patients with stage IV disease were detected (Fig. 6). For one stage I CRC patient, the extract showed no methylation for both the genes. This extract was characterized by a low concentration of total circulating DNA (1.1 ng/μL) and no mutation was detected by NGS either on the plasma extract or on the tissue biopsy, suggesting a disease in the early stages of carcinogenesis. The ten ctDNA in the control group were analyzed and the methylation of the NPY and WIF1 genes was negative (Supplementary data).

Fig. 6
figure6

CRCs ctDNA compared to control group in liquid biopsies. Comparison of NPY (A) and WIF1 (B) hypermethylation in liquid biopsies of patients with a CRC compared to control group by Mann Whitney test. The red line represents the specific threshold of positivity: ≥1 positive droplet for NPY and ≥ 5 positive droplets for WIF1

A significant correlation was observed between the concentration of total circulating DNA in the plasma extracts and the number of positive droplets (p < 0.0001 for NPY and WIF1; non-parametric Spearman’s test). As expected, the correlation between the number of positive droplets and the percentage of mutation found in NGS was not observed (p = 0.0703 for NPY; p = 0.0787 for WIF1; non-parametric Spearman’s test).

Discussion

Methylation of WIF1 and NPY in colorectal tissues

In the cohort, 23 primary colorectal tumor tissues were analyzed associated with 11 adjacent non-tumor tissues to measure DNA hypermethylation of NPY and WIF1, as potential new biomarkers of CRC in liquid biopsies. A significant hypermethylation of NPY and WIF1 in the tumor tissues was demonstrated (p < 0.001 for NPY; p < 0.001 for WIF1) (Fig. 4D). However, a higher than LOB positive droplet counts was found in healthy tissues. This result could be explained by the very high sensitivity of dPCR. Indeed, tissues are considered healthy by microscopic analyzes but some tumor cells, or pre-tumor cells, would be present without any microscopical characteristic. In addition, biopsies of adjacent non-tumor tissues may contain tumor cells and/or ctDNA within their vascularization. This tumor “contamination” of healthy tissue was already found with low positivity [13, 14]. These results are consistent with those of Roperch et al. who set a methylation threshold above this, and considered the threshold of positive result, 25% for NPY and 7% for WIF1, because non-tumor adjacent tissues also had a low percentage of methylation level [13].

Furthermore, a significant correlation between the number of positive droplets for NPY and WIF1 was found (R2 = 0.62, p = 0.0016), suggesting that methylation of both genes is early and concomitant in carcinogenesis. On the other hand, no significant correlation was observed with the MLH1 promoter methylation used as a predictive factor of sporadic forms of CRC, but on the other hand found in MSI CRCs. Thus, methylation of the NPY and WIF1 genes appears to be a process independent of mismatch repair genes methylation and suggests mechanisms of systematic methylation, concerning low significance genes for carcinogenesis (as NPY or WIF1). And a conditioned methylation of some tumor suppressor genes whose repression is necessary for carcinogenesis process. This is confirmed in tumor DNA extracted from a biopsy for which no methylation of the MLH1 gene promoter was found, whereas methylation of the NPY and WIF1 genes was observed.

Significant difference in the level of methylation was not found according to the stage of the tumor. These results are consistent with constant methylation of both genes in tumor DNA. NPY and WIF1 DNA methylation are powerful specific biomarkers of all types of CRCs.

Methylation of NPY and WIF1 on circulating tumor DNA

The method has been validated on tissues and then on ctDNA from CRC patients. All analyzed plasma samples from CRC patients were positive for WIF1 and/or NPY methylation except one stage I patient sample (Fig. 6). This negative DNA extract was very low in total DNA (1.1 ng/μL). The absence of ctDNA in this sample is probably the cause of the negative result [6]. These results were also confirmed in preliminary data on Stilla Application Note [17]. Nevertheless, the presence of methylation of NPY and WIF1 genes in all other samples suggests that methylation process occurs is constant in carcinogenesis. Therefore, the detection of this epigenetic process could be a relevant marker for CRCs screening. Thus, this sensitive and non-invasive technique can be an interesting screening tool for CRCs exploration, and especially in advanced stages that require rapid treatment.

NPY and WIF1’s role in colorectal carcinogenesis

The hypermethylation of NPY promoter in CRCs leads to a strong repression of its transcription (Fig. 1A). The region targeted by our dPCR protocol partially overlaps with the 5’UTR of NPY and is entirely contained within the promoter of NPY (Fig. 1B). The genomic colocation with the promoter could explain the negative correlation between the methylation of the dPCR target and the expression of NPY. Nevertheless, the role of NPY in the tumorigenesis process is not fully elucidated. In vitro, NPY appears to promote tumorigenesis, probably in a neoneurogenesis context in which tumor cells exploit neurotransmitters to generate a pro-tumor environment [18]. NPY repression should thus inhibit tumor proliferation. Paradoxically, NPY appears to reduce the invasive potential of tumor cells in vitro [19]. In the CISTROME database with experimental data, we observed that EP300, EZH2, JARID2, RYBP, PAX5, and SUZ12, might bind the NPY targeted region [20]. Also, in silico analysis shows that this CpG island could interact with several transcription factors (TF) such as CTCF, EZH2, GLIS2, RAD21, ZFP37, ZBT family (ZBTB20, ZBTB26, ZBTB17, ZBTB11) and ZNF family (ZNF777, ZNF335) [20]. The specific methylation of the dPCR targeted region could inhibit the transcription of NPY enhanced by those TF. Currently, only in vitro data are available and the role of NPY in CRCs is still to be defined. By the way, Alshalalfa et al have shown, that in the case of prostate cancer, the decrease of NPY appears to be associated with aggressive phenotype and with a high risk of developing metastasis [21].

Amlal et al. showed that estrogen up-regulates NPY receptor (Y1R) expression through estrogen receptor alpha [22] in breast cancer cell lines. Estrogen plays an important role in the up-regulation of Y1R, which in turn regulates estrogen-induced cell proliferation in breast cancer cells. In another model, estrogen significantly decreased NPY secretion in both the mHypoE-42 and mHypoA-2/12 neurons [23]. These findings indicate that the central anorexigenic action of estrogen occurs at least partially through hypothalamic NPY-synthesizing neurons. Estrogen actions on NPY receptor might affect NPY signaling according to genders. In our study, no signicant differences were observed between female and male patients concerning methylation of NPY (p = 0.055 for non-tumor tissues and p = 0.13 for tumor tissues) (Supplementary data 3A). These observations were confirmed by TCGA-databases analyzes (p = 0.89 for non-tumor tissues and p = 0.69 for tumor tissues) (Supplementary data 3B). We can suppose that gender does not affect the methylation of NPY in CRC carcinogenesis.

Concerning the WIF1, its repression leads to an overexpression of the Wnt signaling pathway thus promoting cell transformation [24]. However, transcriptomic analysis from the Cancer Genome Atlas (TCGA) shows overexpression of WIF1 in CRCs (Fig. 5B). The dPCR target is entirely contained within the 5’UTR of WIF1 but does not overlap the promoter of WIF1 (Fig. 1A). Thus, WIF1 is a tumor suppressor gene whose expression should be rather inhibited in tumor tissues. Therefore, regulatory sequences have to be hypermethylated. We could suggest that sequences analysed by dPCR are not implicated in the regulation of WIF1 expression and could result from systematic methylation. Hypermethylation of dPCR targeted WIF1 region would therefore not lead to repression of the gene. In CISTROME database, WIF1 hypermethylated region is experimentally associated with some proteins such as EP300, EZH2, HDAC2, HIC1, JARID2, KDM2B, MBD2, PRDM11, RYBP, SMAD2, SPDEF, SRF, SUZ12, ZMYND8, ZNF180, ZNF189 and ZNF483 [20]. In silico analysis shows that CpG region targeted by dPCR could interact with several TF such as CREB1, CTCF, EGR2, EZH2, GLIS2, HIC1, KDM1A, KLF9, KLF16, PATZ1, POLR2A, TBP, ZBTB family (ZBTB8A, ZBTB17, ZBTB26, ZBTB33, ZBTB48), ZEB2, ZFHX2, ZFP69B, ZFP37ZSCAN21 and ZNF family (ZNF398, ZNF335, ZNF341, ZNF501, ZNF513, ZNF600, ZNF692, ZNF777, ZNF792) [20]. Feng et al demonstrates that miR-590-3p regulates colon cancer progression via WIF1 which suggests that miR-590-3p may be a promising candidate for therapeutic applications in colon cancer treatment [25]. In nasopharyngeal cancers and gastric carcinoma cell lines the promoters of WIF1 is hypermethylated, and his expression is regulated by miR-BART19-3p [26]. Also the miR-552-5p promoted osteosarcoma development and progression by inhibiting WIF1 [27]. These studies show that WIF1 could be highly regulated by post-transcriptional factors. These data only provide information on the level of mRNA expression but not the protein functionality.

Thus, the hypermethylated promoters of NPY and WIF1 are specific early markers of colorectal cancers but their roles in CRCS carcinogenesis are not clearly established.

Limitations of the study

The size of our cohort is sufficient to demonstrate the efficiency of our technique for the detection of NPY and WIF1 methylation status. However, it is difficult to make subgroup comparisons. Nevertheless, our study confirms previous studies results suggesting that methylation of one or both genes seems to be a relevant biomarker to detect the presence of ctDNA in plasma liquid biopsies. Our study is robust and highlights an original and powerful technique in the detection of specific methylation profile of CRC. Roperch and al [13]. tested 161 sera from patients with normal colonoscopy using Methylation Specific PCR. They showed a specificity of 80 and 95% for NPY and WIF1 respectively. Garrigou et al. analyzed 46 plasmas from non-cancer patients with their dPCR technique. Only 3 patients had a higher than the LOB droplet count for the NPY gene, i.e. a specificity of 93%. The specificity of the WIF1 gene was 100% [14].

Many exogenous factors known to modulate DNA methylation were not included in our study. Indeed, many links between lifestyle and epigenetic modifications have been shown [28]. For example, tobacco [28] or alcohol [29] consumption have been shown to modulate DNA methylation. The comparison between consumers and non-consumers could help to understand if by modifying the methylation profiles, the consumption of tobacco or alcohol, could generate false positive results in our technical approach.

Availability of data and materials

The datasets generated and analyzed during this study (birthdate, admission date, discharge date, date of death …), are available from the corresponding author on reasonable request.

Abbreviations

ADC:

Adenocarcinoma

ADC-PD:

Partially differentiated adenocarcinoma

ADC-WD:

Well-differentiated adenocarcinoma

AUC:

Area under the curve

CRC:

Colorectal cancer

ctDNA:

Circulating tumor DNA

dPCR:

Digital Polymerase chain reaction

FFPE:

Formalin-fixed paraffin-embedded

LOB:

Limit of blank

MSS:

Microsatellite stable

MSI:

Microsatellite instability

MS-PCR:

Methylation Specific-PCR

NGS:

Next generation sequencing

NPY:

Neuropeptide Y

ROC:

Receiver operatoring characteristic

WIF1:

Wnt inhibitory factor 1

References

  1. 1.

    Ganesh K, Stadler ZK, Cercek A, Mendelsohn RB, Shia J, Segal NH, et al. Immunotherapy in colorectal cancer: rationale, challenges and potential. Nat Rev Gastroenterol Hepatol. 2019;16(6):361–75. https://doi.org/10.1038/s41575-019-0126-x.

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Cabel L, Proudhon C, Romano E, Girard N, Lantz O, Stern M-H, et al. Clinical potential of circulating tumour DNA in patients receiving anticancer immunotherapy. Nat Rev Clin Oncol oct. 2018;15(10):639–50. https://doi.org/10.1038/s41571-018-0074-3.

    CAS  Article  Google Scholar 

  3. 3.

    Diaz LA, Bardelli A. Liquid Biopsies: Genotyping Circulating Tumor DNA. J Clin Oncol. 2014;32(6):579–86.

    Article  Google Scholar 

  4. 4.

    Chen M, Zhao H. Next-generation sequencing in liquid biopsy: cancer screening and early detection. Hum Genomics. 2019;13(1):34.

    Article  Google Scholar 

  5. 5.

    Postel M, Roosen A, Laurent-Puig P, Taly V, Wang-Renault S-F. Droplet-based digital PCR and next generation sequencing for monitoring circulating tumor DNA: a cancer diagnostic perspective. Expert Rev Mol Diagn. 2018;18(1):7–17. https://doi.org/10.1080/14737159.2018.1400384.

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Moati E, Blons H, Taly V, Garlan F, Wang-Renault S-F, Pietrasz D, et al. Plasma clearance of RAS mutation under therapeutic pressure is a rare event in metastatic colorectal cancer. Int J Cancer. 2020;147(4):1185–9. https://doi.org/10.1002/ijc.32657.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Costa-Pinheiro P, Montezuma D, Henrique R, Jerónimo C. Diagnostic and prognostic epigenetic biomarkers in cancer. Epigenomics. 2015;7(6):1003–15. https://doi.org/10.2217/epi.15.56.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Ding W, Chen G, Shi T. Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis. Epigenetics. 2019;14(1):67–80. https://doi.org/10.1080/15592294.2019.1568178.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Fernandez AF, Assenov Y, Martin-Subero JI, Balint B, Siebert R, Taniguchi H, et al. A DNA methylation fingerprint of 1628 human samples. Genome Res févr. 2012;22(2):407–19. https://doi.org/10.1101/gr.119867.110.

    CAS  Article  Google Scholar 

  10. 10.

    Ehrlich M. DNA hypomethylation in cancer cells. Epigenomics déc. 2009;1(2):239–59. https://doi.org/10.2217/epi.09.33.

    CAS  Article  Google Scholar 

  11. 11.

    Weber M, Hellmann I, Stadler MB, Ramos L, Paabo S, Rebhan M, et al. Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome. Nat Genet. 2007;39(4):10–466. https://doi.org/10.1038/ng1990.

    CAS  Article  Google Scholar 

  12. 12.

    Kulis M, Esteller M. DNA methylation and cancer. Adv Genet. 2010;70:27–56. https://doi.org/10.1016/B978-0-12-380866-0.60002-2.

    Article  PubMed  Google Scholar 

  13. 13.

    Roperch J-P, Incitti R, Forbin S, Bard F, Mansour H, Mesli F, et al. Aberrant methylation of NPY, PENK, and WIF1 as a promising marker for blood-based diagnosis of colorectal cancer. BMC Cancer. 2013;13:566.

    Article  Google Scholar 

  14. 14.

    Garrigou S, Perkins G, Garlan F, Normand C, Didelot A, Le Corre D, et al. A study of Hypermethylated circulating tumor DNA as a universal colorectal Cancer biomarker. Clin Chem. 2016;62(8):1129–39. https://doi.org/10.1373/clinchem.2015.253609.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12).

  16. 16.

    Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut avr. 2017;66(4):683–91. https://doi.org/10.1136/gutjnl-2015-310912.

    Article  Google Scholar 

  17. 17.

    FORM : Detection of hypermethylated circulating tumor DNA by crystal digital PCR™. Stilla. https://www.stillatechnologies.com/form-detection-of-hypermethylated-circulating-tumor-dna-by-crystal-digital-pcr/.

  18. 18.

    Jeppsson S, Srinivasan S, Chandrasekharan B. Neuropeptide Y (NPY) promotes inflammation-induced tumorigenesis by enhancing epithelial cell proliferation. Am J Physiol Gastrointest Liver Physiol. 2017;312(2):G103–11.

    Article  Google Scholar 

  19. 19.

    Ogasawara M, Murata J, Ayukawa K, Saimi I. Differential effect of intestinal neuropeptides on invasion and migration of colon carcinoma cells in vitro. Cancer Lett. 1997;116(1):111–6.

    CAS  Article  Google Scholar 

  20. 20.

    Wang S, Sun H, Ma J, Zang C, Wang C, Wang J, et al. Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nat Protoc déc. 2013;8(12):2502–15. https://doi.org/10.1038/nprot.2013.150.

    CAS  Article  Google Scholar 

  21. 21.

    Alshalalfa M, Nguyen PL, Beltran H, Chen WS, Davicioni E, Zhao SG, et al. Transcriptomic and clinical characterization of neuropeptide Y (NPY) expression in localized and metastatic prostate cancer: identification of novel prostate cancer subtype with clinical implications. Eur Urol Oncol juill. 2019;2(4):405–12. https://doi.org/10.1016/j.euo.2019.05.001.

    Article  Google Scholar 

  22. 22.

    Amlal H, Faroqui S, Balasubramaniam A, Sheriff S. Estrogen Up-regulates Neuropeptide Y Y1 Receptor Expression in a Human Breast Cancer Cell Line. Cancer Res. 2006;66(7):3706–14.

    CAS  Article  Google Scholar 

  23. 23.

    Dhillon SS, Belsham DD. Estrogen inhibits NPY secretion through membrane-associated estrogen receptor (ER)-α in clonal, immortalized hypothalamic neurons. Int J Obes févr. 2011;35(2):198–207. https://doi.org/10.1038/ijo.2010.124.

    CAS  Article  Google Scholar 

  24. 24.

    Wissmann C, Wild PJ, Kaiser S, Roepcke S, Stoehr R, Woenckhaus M, et al. WIF1, a component of the Wnt pathway, is down-regulated in prostate, breast, lung, and bladder cancer. J Pathol. 2003;201(2):204–12. https://doi.org/10.1002/path.1449.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Feng Z-Y, Xu X-H, Cen D-Z, Luo C-Y, Wu S-B. miR-590-3p promotes colon cancer cell proliferation via Wnt/β-catenin signaling pathway by inhibiting WIF1 and DKK1. European review for medical and pharmacological. Sciences. 2017;21:4844–52.

    Google Scholar 

  26. 26.

    Zhao Z, Liu W, Liu J, Wang J, Luo B. The effect of EBV on WIF1, NLK, and APC gene methylation and expression in gastric carcinoma and nasopharyngeal cancer. J Med Virol. 2017;89(10):1844–51. https://doi.org/10.1002/jmv.24863.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Cai W, Xu Y, Yin J, Zuo W, Su Z. miR-552-5p facilitates osteosarcoma cell proliferation and metastasis by targeting WIF1. Exp Ther Med. 2019;17(5):3781–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Alegría-Torres JA, Baccarelli A, Bollati V. Epigenetics and lifestyle. Epigenomics. 2011;3(3):267–77. https://doi.org/10.2217/epi.11.22.

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Varela-Rey M, Woodhoo A, Martinez-Chantar M-L, Mato JM, Lu SC. Alcohol, DNA methylation, and cancer. Alcohol Res Curr Rev. 2013;35(1):25–35.

    Google Scholar 

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Acknowledgments

We thank all patients who agreed to participate in this observational study. The authors are grateful to the anatomopathology department and the “Tumorothèque Régionale de Franche-Comté” (Franck Monnien) of Besançon CHU for their participation in the samples selection. The authors also thank Magnin Sandrine, PhD. and her team for their technical support and their expertise. And Dr. Peixoto Paul for his support. This study was also supported by CELIA grant of Besançon university hospital and by Emergence project of “Région Bourgogne Franche-Comté” .

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Authors

Contributions

Conception and design: SZ, FM, BC. Development of methodology: OA, FM, ZS, EH. Acquisition of data: FM, ZS. Analysis and interpretation of data: OA, SZ, FM, FJP. Writing, review, and/or revision of the manuscript: AO, FM, SZ, PJL, HE. Administrative, technical, or material support: SZ, BL, PJL. Study supervision: SZ.

Corresponding author

Correspondence to Zohair Selmani.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the national research committee and with the 1964 Helsinki Declaration and its later amendments. In France, this search is considered as a non-interventional study according to European legislation. All patients were individually informed that their data should be used to scientific research. All experimental protocols were approved by the scientific board of the regional biobank of Franche-Comté, France (registration number BB-0033-00024, Tumorothèque Régionale de Franche-Comté) that ensures patients informed consent.

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The authors declare that they have no competing interests.

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Overs, A., Flammang, M., Hervouet, E. et al. The detection of specific hypermethylated WIF1 and NPY genes in circulating DNA by crystal digital PCR™ is a powerful new tool for colorectal cancer diagnosis and screening. BMC Cancer 21, 1092 (2021). https://doi.org/10.1186/s12885-021-08816-2

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Keywords

  • Colorectal cancer
  • Liquid biopsy
  • Epigenetics
  • DNA methylation
  • NPY
  • WIF1
  • Digital PCR