Basic Study Open Access
Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Oct 21, 2017; 23(39): 7087-7097
Published online Oct 21, 2017. doi: 10.3748/wjg.v23.i39.7087
Detection of KRAS G12D in colorectal cancer stool by droplet digital PCR
Susana Olmedillas-López, Luz Vega-Clemente, Alejandro Villagrasa, Mariano García-Arranz, Damián García-Olmo, Foundation Health Research Institute-Fundación Jiménez Díaz University Hospital, Madrid 28040, Spain
Dennis César Lévano-Linares, Mariano García-Arranz, Damián García-Olmo, Department of Surgery, School of Medicine, Universidad Autónoma de Madrid, Madrid 28029, Spain
Dennis César Lévano-Linares, Jaime Ruíz-Tovar, Department of Surgery, Rey Juan Carlos University Hospital, Madrid 28933, Spain
Carmen Laura Aúz Alexandre, Department of Pathology, Fundación Jiménez Díaz University Hospital, Madrid 28040, Spain
Edurne León Sánchez, Department of Biomedicine and Biotechnology, Universidad de Alcalá, Madrid 28805, Spain
Damián García-Olmo, Department of Surgery, Fundación Jiménez Díaz University Hospital, Madrid 28040, Spain
ORCID number: Susana Olmedillas-López (0000-0002-6535-5852); Dennis César Lévano-Linares (0000-0003-3027-4005); Carmen Laura Aúz Alexandre (0000-0001-5045-1326); Luz Vega-Clemente (0000-0002-8558-1937); Edurne León Sánchez (0000-0002-8279-4881); Alejandro Villagrasa (0000-0002-2683-4738); Jaime Ruíz-Tovar (0000-0002-8505-2605); Mariano García-Arranz (0000-0002-6266-9055); Damian Garcia-Olmo (0000-0002-9369-2338).
Author contributions: Olmedillas-López S and Lévano-Linares DC contributed equally to this work; Olmedillas-López S, Lévano-Linares DC, García-Arranz M and García-Olmo D conceived and designed the experiments; Olmedillas-López S, Aúz Alexandre CL, Vega-Clemente L, León Sánchez E and Villagrasa A performed the experiments; Olmedillas-López S, Lévano-Linares DC, Ruíz-Tovar J, García-Arranz M and García-Olmo D analyzed the data; Olmedillas-López S and Lévano-Linares DC wrote the paper.
Supported by “Fondo de Investigaciones Sanitarias (FIS)-FEDER”, Ministry of Health, Spain, No. PI13/01924 to García-Olmo D; and RETIC Program of ISCIII-FEDER, No. RD12/0019/0035 to Olmedillas-López S.
Institutional review board statement: This study was reviewed and approved by the Institutional Ethics Committee for Clinical Research of the Fundación Jiménez Díaz University Hospital (FJD) (PIC 63/2016_FJD).
Conflict-of-interest statement: The authors have no conflict of interest to declare.
Data sharing statement: Individual participant consent was not obtained for data sharing but the presented data are anonymized and there is no possibility of identification. No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Susana Olmedillas-López, PhD, Postdoc Researcher, Foundation Health Research Institute-Fundación Jiménez Díaz University Hospital, Avda. Reyes Católicos 2, Madrid 28040, Spain. susana.olmedillas@fjd.es
Telephone: +34-91-5504800-2781 Fax: +34-91-5505353
Received: June 28, 2017
Peer-review started: June 28, 2017
First decision: August 15, 2017
Revised: September 15, 2017
Accepted: September 26, 2017
Article in press: September 26, 2017
Published online: October 21, 2017
Processing time: 115 Days and 21.2 Hours

Abstract
AIM

To assess KRAS G12D mutation detection by droplet digital PCR (ddPCR) in stool-derived DNA from colorectal cancer (CRC) patients.

METHODS

In this study, tumor tissue and stool samples were collected from 70 patients with stage I-IV CRC diagnosed by preoperative biopsy. KRAS mutational status was determined by pyrosequencing analysis of DNA obtained from formalin-fixed paraffin-embedded (FFPE) tumor tissues. The KRAS G12D mutation was then analyzed by ddPCR in FFPE tumors and stool-derived DNA from patients with this point mutation. Wild-type (WT) tumors, as determined by pyrosequencing, were included as controls; analysis of FFPE tissue and stool-derived DNA by ddPCR was performed for these patients as well.

RESULTS

Among the total 70 patients included, KRAS mutations were detected by pyrosequencing in 32 (45.71%), whereas 38 (54.29%) had WT tumors. The frequency of KRAS mutations was higher in left-sided tumors (11 located in the right colon, 15 in the left, and 6 in the rectum). The predominant point mutation was KRAS G12D (14.29%, n = 10), which was more frequent in early-stage tumors (I-IIA, n = 7). In agreement with pyrosequencing results, the KRAS G12D mutation was detected by ddPCR in FFPE tumor-derived DNA, and only a residual number of mutated copies was found in WT controls. The KRAS G12D mutation was also detected in stool-derived DNA in 80% of all fecal samples from CRC patients with this point mutation.

CONCLUSION

ddPCR is a reliable and sensitive method to analyze KRAS G12D mutation in stool-derived DNA from CRC patients, especially at early stages. This non-invasive approach is potentially applicable to other relevant biomarkers for CRC management.

Key Words: Droplet digital PCR, KRAS, Stool, Formalin-fixed paraffin-embedded, Pyrosequencing, Colorectal cancer

Core tip: The potential of droplet digital PCR (ddPCR) to detect KRAS G12D mutation in stool DNA from colorectal cancer (CRC) patients was examined as a proof-of-concept for the applicability of this technology to study DNA biomarkers in stool-derived DNA. It was shown that KRAS G12D detection in stool-derived DNA from CRC patients by ddPCR is feasible and provides comparable results to the analysis of formalin-fixed paraffin-embedded tissue by pyrosequencing. These results suggest that analysis of KRAS mutations and other molecular biomarkers in stool by ddPCR could represent a complementary non-invasive approach to standard screening tests for CRC.



INTRODUCTION

Colorectal cancer (CRC) is the second and third most common cancer in women and men, respectively, with more than one million cases diagnosed each year worldwide[1]. Current therapeutic options have increased overall survival (OS), but have also made clinical decisions more complex, especially in patients with an initial diagnosis of metastatic colorectal cancer (mCRC)[2]. Biological agents targeting the epidermal growth factor receptor (EGFR), such as cetuximab and panitumumab, used either as monotherapy or in combination with standard chemotherapy, are indicated in mCRC patients with RAS (KRAS and NRAS) or KRAS wild-type (WT) tumors, respectively[3,4]. These strategies significantly improve progression-free survival (PFS) and OS in KRAS WT mCRC patients depending on the therapeutic regimen applied (chemotherapy and line of treatment)[2,5].

KRAS oncogene mutations, mostly found in codons 12 and 13[6], have been described in approximately 30%-40% of CRC tumors[7-9]. These mutations are associated with absence of response to therapy with biological agents[10,11] and have been correlated with worse prognosis[12,13]. In fact, in Europe and the United States, monoclonal antibody-based therapy has been restricted to patients with WT tumors[14], as when administered in association with standard chemotherapy, this treatment may result in an increased cost and toxicity[10]. Drug resistance can occur months after start of combined therapy, likely due to intratumoral heterogeneity and proliferation of small sub-groups of clonal cells carrying resistance mutations that are difficult to identify by most of the currently applied methods[14,15]. Therefore, highly sensitive and specific methodologies are needed to detect and quantify molecular markers, including KRAS mutations, which play a pivotal role in early detection and clinical management of CRC patients.

Droplet digital PCR (ddPCR) is increasingly seen as one of the most powerful techniques to accurately detect a wide variety of genetic alterations in many cancer types. These molecular biomarkers have been analyzed by ddPCR in different body fluids such as blood, urine, cerebrospinal fluid, pleural effusions, ascites and sputum (reviewed in[16]).

Stool-derived DNA is a potential non-invasive alternative source of DNA for tumor genotyping in CRC due to the high rate of exfoliation of tumor cells into the bowel lumen[17]. Digital PCR was first described in 1999 by Vogelstein and Kinzler in a study aimed at identifying KRAS in DNA obtained from fecal samples of CRC patients[18]. Based on the isolation of single molecules by limiting dilution of DNA samples and individual amplification by PCR, mutations were detected using fluorescent probes. However, this methodology was found to be quite laborious and difficult to translate into clinical practice[19]. The introduction of new instrumentation involving nanofluidic devices and improved emulsion chemistries has allowed for more widespread use of digital PCR, giving way to the current commercially available platforms[19]; of these, emulsion-based ddPCR has undergone huge growth in cancer research. In fact, a recent study has investigated the application of ddPCR to quantify mRNA biomarkers in stool from patients with CRC as a potential non-invasive screening test[17]. Thus, analysis of DNA obtained from fecal samples in patients with CRC may complement currently used procedures for diagnosis and disease follow-up.

In our experience, ddPCR has shown high sensitivity for detection of mutated KRAS alleles in circulating cell-free DNA (cfDNA) in plasma from CRC patients[20]. However, early-stage patients sometimes have undetectable levels of circulating tumor DNA (ctDNA)[20,21]. The aim of this study was to evaluate the feasibility of KRAS G12D mutation detection in stool-derived DNA from CRC patients by ddPCR, including early-stage patients.

MATERIALS AND METHODS
Patients

Seventy CRC patients were consecutively included in this study from 2014 to 2015 in the Department of General Surgery at Fundación Jiménez Díaz University Hospital (Madrid, Spain). Inclusion criteria were endoscopic histological diagnosis of CRC and eligibility for primary tumor resection with curative intent. Patients with primary tumors located in the rectum who had received prior neoadjuvant treatment were excluded. All subjects signed an informed consent in accordance with a protocol approved by the Ethics Committee for Clinical Research of this institution (PIC 63/2016_FJD).

Fecal sample collection

All fecal samples were collected during hospitalization before surgery without any bowel preparation (with the exception of patient 17, who was subjected to cathartic preparation due to an oversight). Stool samples were collected in sterile containers and stored at -20 °C until analysis.

DNA extraction

A total amount of 200-500 mg of fecal sample was used for DNA extraction. DNA was isolated using the QIAamp DNA Stool Mini kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. DNA from the LS-174T cell line (kindly provided by the Translational Oncology Division, OncoHealth Institute, IIS-FJD, which had previously purchased this cell line from the American Type Culture Collection, ATCC in Manassas, VA, United States) and DNA from peripheral blood mononuclear cells of a healthy donor were extracted with the QIAamp DNeasy Blood and Tissue Kit (Qiagen) according to the manufacturer’s protocol. DNA from formalin-fixed paraffin-embedded (FFPE) tumors was extracted using the Cobas DNA Sample Preparation Kit (Roche Molecular Systems, Inc., Branchburg, NJ, United States) following the manufacturer's instructions. The quantity and purity of the DNA obtained was estimated by NanoDrop (ND-2000 UV-Vis Spectrophotometer; Nanodrop Technologies Inc., Waltham, MA, United States).

Mutation detection in FFPE tumor samples by pyrosequencing

Quantitative analysis of KRAS mutations was performed by pyrosequencing in accordance with routine practice at the Department of Pathology at Fundación Jiménez Díaz University Hospital, using the CE-IVD marked Therascreen KRAS Pyro kit (Qiagen), according to the manufacturer’s protocols. Each PCR product was analyzed by pyrosequencing using the Therascreen KRAS Pyro reagents (Qiagen), Streptavidin Sepharose High Performance (GE Healthcare Bio-Science AB, Uppsala, Sweden), and a PyroMark Q24 instrument (Qiagen).

Mutation detection in FFPE tumor tissues and stool samples by ddPCR

ddPCR assays were performed using the QX200 Droplet Digital PCR System (Bio-Rad, Hercules, CA, United States) with the Prime-PCR™ ddPCR™ Mutation Detection Assay Kit (Bio-Rad); amplicon size was 57 bp. DNA from LS-174T, a human colon adenocarcinoma KRAS G12D heterozygous cell line, was used as a positive control. KRAS WT control DNA was obtained from peripheral blood mononuclear cells of a healthy donor. Background was measured by adding water to the reaction mixture instead of DNA. The PCR reaction mixture (20 μL) contained 10 μL of ddPCR Supermix (no dUTP) for probes, 1 μL of each primer/probe mix (target and reference, labeled with HEX and FAM fluorophores, respectively), and 2-8 μL of stool-extracted DNA. Different amounts of stool-derived DNA were assayed per sample, as the proportion of human DNA with respect to bacterial DNA was unknown and could vary among patients. A total amount of 100 ng of cell-derived control DNA was added per well. In case of DNA from FFPE tumors, 50 ng per well was used. Thermal cycling consisted of 10 min at 95 °C, 40 cycles of 94 °C for 30 s, and 55 °C for 60 s. Results were analyzed using QuantaSoft v.1.7 software (Bio-Rad) and reported as number of copies per 20 μL reaction as well as copies per ng of DNA. Three to four replicates of each stool sample were analyzed. FFPE tumors and controls were assayed in duplicate.

Statistical analysis

A non-parametric Mann-Whitney test for significance was performed using R software.

RESULTS
Patient characteristics

A total of 70 stool and tissue samples from CRC patients were collected and included in the study. All patients were classified according to the distance between the primary tumor and anal margin (cm) reported in the preoperative colonoscopy. Forty-one (58.57%) were male, with a median age of 73 years. Only 5 (7.14%) had a diagnosis of mCRC at baseline.

The patients included in this study were representative of all tumor locations, with 28 (40%) located in the right colon, 34 (48.57%) in the left colon, and 8 (11.43%) in the rectum. Interestingly, 45 (64.29%) patients were diagnosed at an early stage (I-IIA). Clinical and pathological features are summarized in Table 1.

Table 1 Patient characteristics.
Colorectal cancer patients, n = 70
Right colon, n = 28Left colon, n = 34Rectum, n = 8
SexFemale13133
Male15215
Age (mean)76.8972.2670.63
pTT1342
T2692
T316183
T4331
pNN020228
N+812-
StageI9104
IIa9103
IIb111
IIIa13-
IIIb45-
IIIc22-
IV23-
KRAS statusMutant11156
Wild-type17192
KRAS mutations in FFPE tumor samples analyzed by pyrosequencing

KRAS mutations were found in the tumors of 32 patients (45.71%), including 11 in the right colon, 15 in the left, and 6 in the rectum. Most mutations were located at codon 12 (n = 17, 53.12%) or codon 13 (n = 6, 18.75%). The most prevalent mutation was G12D (n = 10, 14.29%). Two were located in the right colon, 6 in the left colon, and 2 in the rectum. This mutation was found more frequently in early-stage tumors (I-IIA, n = 7). The incidence of the different types of mutations is shown in Table 2.

Table 2 KRAS mutational status by pyrosequencing.
KRAS wild-typeKRAS mutations
Codon 12
Codon 13
Others
G12DG12VG12RG12SG13DG13RA146VA146TA59TQ61RQ61HQ61L
Right colon17201031110110
Left colon19650010111000
Rectum2200110000011
1051151221121
Total38 (54.29%)32 (45.71%)
KRAS G12D detection in FFPE tumor samples by ddPCR

FFPE tumors from patients found to have a KRAS G12D mutation by pyrosequencing were analyzed using ddPCR. Five CRC patients with WT KRAS exon 2 tumors were selected as controls. One control carried a KRAS Q61L mutation (exon 3) that did not interfere with our assays. Results obtained from ddPCR analysis of FFPE tumor DNA from these 15 CRC patients were in agreement with pyrosequencing results. A residual number of KRAS G12D copies was found in WT tumors. Due to this level of unspecific background signal, mean copies/ng DNA from control patients plus 2 standard deviation (SD) was considered as a threshold for positivity (0.41 copies/ng DNA). All samples from patients with G12D-positive tumors were above this threshold and showed a significantly higher number of mutant copies/ng DNA than patients with WT KRAS tumors (median, 106 and 0.19 copies/ng DNA, respectively; P = 0.001). However, the difference in number of WT KRAS copies/ng DNA between both groups was not statistically significant (210.00 copies/ng vs 208.40 copies/ng DNA, median; P = 0.699).

KRAS G12D detection in stool samples by ddPCR

Subsequently, we analyzed the presence of the KRAS G12D mutation by ddPCR analysis of fecal samples from the 10 patients with mutated tumors by pyrosequencing. Stool DNA from 5 patients with tumors carrying the WT KRAS exon 2 were also included as controls. A limited number of KRAS G12D-positive events were detected in stool DNA from control WT KRAS exon 2 samples. Consequently, mean control value plus 2 SD was established as the positivity threshold. Thus, in our study, stool samples were required to contain more than 1.9 copies/20 μL of reaction to be considered positive for the mutation. According to this threshold, which was equivalent to > 3 positive events per sample, the KRAS G12D mutation was detected in 8 of 10 patients. Of these 8 positive samples, 6 were from early-stage tumors. Samples from Patients 46 and 64 were considered negative because they had values less than or equal to the positivity threshold. KRAS G12D mutation levels in stool samples are shown in Tables 3 and 4. The median number of copies of KRAS G12D/20 μL of reaction as well as copies/ng of stool DNA in control patients differed significantly from those with mutated tumors (P = 0.017). The KRAS WT sequence was also detected in stool samples of all CRC patients, though there were no significant differences in the median number of KRAS WT copies/ng of stool DNA between both groups (P = 0.129).

Table 3 KRAS G12D mutation levels in DNA from stool samples of wild-type control patients.
G12D
Wild-type
SingleMergedSingleMerged
PatientTumor locationTumor stagePositive eventsCopies/μLCopies/20 μL reactionPositive eventsCopies/μLCopies/20 μL reactionCopies/ng DNAPositive eventsCopies/μLCopies/20 μL reactionPositiveeventsCopies/μLCopies/20 μL reactionCopies/ng DNA

53LeftI10.1230.071.400.01194918046910.50210.001.615
20.173.41210.8216
0001169.9198
00013612.1242
56LeftIIA10.081.610.020.400.003171.428761.5631.200.240
000252.142
000161.326
000181.428
63RightIIA10.081.610.020.420.00325820.440895720.30406.003.123
00022222.1442
00021719380
00026019.9398
71RightIIIB10.081.630.061.200.009896.71343777.20144.001.108
20.1531047.9158
000936.9138
000917.3146
96LeftIV10.091.830.061.200.009323601332.8456.800.437
10.081.6332.652
10.091.834360
000342.958
Table 4 KRAS G12D mutation levels in DNA from stool samples of patients with KRAS G12D mutated tumors.
G12D
Wild-type
Single
Mergedsingle
Merged
PatientTumor locationTumor stagePositive eventsCopies/μLCopies/20 μL reactionPositive eventsCopies/μLCopies/20 μL reactionCopies/ng DNAPositive eventsCopies/μLCopies/20 μL reactionPositive eventsCopies/μLCopies/20 μL reactionCopies/ng DNA
12RectumI40.326.4140.377.400.05115512.625249313.10262.001.819
50.397.815812.5250
50.397.818014.1282
17LeftI1147951900484997.201944.0041.3624684446892019664456.009120.00194.043
124398196049964589160
126999198050944609200
119097194048904619220
29LeftIIIB50.418.2110.306.000.024947.71542577.10142.000.577
30.244.8907.4148
30.255736.2124
30RightI60.5711.4180.5410.800.01723822.845675723.10462.000.728
70.6412.826824.8496
50.438.625121.8436
43RightIIIC60.5911.8190.5911.800.03541842840139344.10882.002.602
80.71449245.5910
50.469.248344.8896
461LeftIIC10.091.830.091.800.0148171402657.80156.001.238
10.091.8978.3166
10.091.8878.2164
51RectumI13120470.9018.000.295129210320605110102.602052.0033.639
120.91812911022040
90.6813.612971022040
1312012301032060
641LeftI00000.000.000.0001411224065312.20244.001.877
00016312.1242
00015411.4228
00019513.3266
70LeftI111.122451.3727.400.036251528256408516294.005880.007.656
241.93833133056100
1012026882915820
75LeftIIA000110.336.600.03230427.254496429.00580.002.788
20.183.632629.8596
90.81633430.1602

In summary, the results of pyrosequencing were in 100% agreement with ddPCR analysis in FFPE tissues, whereas ddPCR detected the KRAS mutation in 8 out of 10 stool samples.

DISCUSSION

Despite the advances made in CRC research, the disease remains a major cause of death worldwide. Recently, the analysis of KRAS oncogene mutations has taken on a major prognostic role in CRC clinical management[22] owing to the fact that the presence of these mutations, which have been described in approximately 30%-40% of cases[7,9,23], could determine the absence of response to anti-EGFR therapies and worse outcome in cases of metastatic disease[10-13]. The most frequent KRAS mutations are located at codons 12 and 13; of these, G12D and G13D are particularly relevant, representing around 13%-14% and 6%-7% of all cases, respectively[7,23]. Moreover, worse prognosis has been documented among patients with tumors with the G12D mutation[8,23]. In agreement with previous observations, the incidence of KRAS G12D mutation in our study population was 14.29%.

Molecular biomarkers in blood and stool may be used as a complementary screening strategy and prognostic tool for the prediction of clinical outcome in patients with or at high risk for CRC[24]. Not only in CRC, but also in many other human malignancies, the analysis of molecular biomarkers in plasma and other body fluids is attracting increasing interest as a highly valuable, non-invasive predictive tool for monitoring disease progression and response to treatment[16]. In CRC, KRAS mutations have been analyzed in blood, both in DNA obtained from circulating tumor cells[25] and in cfDNA[26]. KRAS-mutation detection by digital PCR has been described using several commercially available platforms[14,27-32], most of which are focused on detecting mutations in plasma. One of these strategies is ddPCR, which has shown a remarkably high sensitivity when detecting these minority KRAS alleles present at low levels in plasma DNA.

In a previous study, using ddPCR, we detected the KRAS G12V mutation in plasma cfDNA from 9 of 10 patients whose tumors were also mutated[20]. In this study, we found that metastatic patients had a significantly higher number of mutated copies in circulating cfDNA than M0 patients. The only negative sample was obtained from a T1N0M0 patient. These results are in line with other studies: Bettegowda et al[21] also reported that ctDNA in plasma increases with disease stage, and only 47% of early-stage patients with a wide variety of cancers had detectable levels of ctDNA. Similarly, Galanopoulos et al[26] recently described that the KRAS codon 12 mutation rate in cfDNA is significantly higher in CRC patients compared to healthy subjects, though this methodology seems to have limited potential for predicting the existence of premalignant lesions (neoplastic colonic polyps). Taken together, these findings suggest that at early disease stages, levels of mutated copies in circulating cfDNA may be, in some cases, too low for detection. Thus, alternative non-invasive methods are still needed.

Interestingly, in a very recent study, ddPCR was also used to quantify an mRNA biomarker, ITGA6, in stool from patients with CRC[17]. Tumor-derived nucleic acids present in stool samples come from the exfoliation of tumor cells of the intestinal mucosa and are a non-invasive, alternative source of genetic material for KRAS oncogene mutation screening in CRC patients[33]. Exfoliation of colonocytes into the large bowel lumen is a continuous, naturally-occurring phenomenon that seems to be exacerbated in tumors[34,35]. Thus, colonocyte shedding from malignant lesions is more frequent than from healthy mucosa[36,37]. Hypothetically, DNA from colorectal tumors should be shed into the bowel fecal content before reaching the bloodstream. This would make testing stool DNA for CRC screening more time-sensitive than plasma or other biological fluids[38].

The proof-of-concept study for stool DNA analysis for CRC detection screened 15 point mutations in several genes, including KRAS[39]. Subsequently, several case-control and prospective studies[40-42] led to the 2014 approval by the United States Food and Drug Administration of a fecal DNA analysis system called Cologuard (Exact Sciences Corporation, Madison, WI, United States) for CRC detection. This system includes an immunochemical assay for human hemoglobin and molecular biomarkers associated with CRC, such as methylation markers (BMP3 and NFRG4 gene promoter regions), KRAS mutations, and β-actin. The test is based on amplification and detection by Quantitative Allele-specific Real-time Target and Signal Amplification (QuARTS) technology. However, this system still has limited application in clinical practice due to its elevated cost. Additionally, the technical difficulties of this test include the need for a large volume of stool sample and the high rate of false-positive results, creating a need for more confirmative colonoscopies and additional costs[38]. Further studies evaluating the cost-effectiveness of this test for large-scale population screening are needed[43].

Fecal DNA analysis for mutation detection has also been reported using several digital PCR systems[18,27,44-48], the first of which were the studies carried out by Vogelstein and Kinzler[18,44], which led to the development of BEAMing (named for ‘beads, emulsions, amplification, and magnetics’)[27]. Other examples are target-enriched multiplex PCR (Tem-PCR)[47], MDHB (multiplex digital PCR coupled with hydrogel bead-array)[46], and MLPA-DABA (multiplex ligation-dependent probe amplification-digital amplification coupled with hydrogel bead-array)[48]. It is worth mentioning that, to date, none of these systems has been further developed and subjected to clinical validation for stool DNA screening.

In our study, DNA from fecal samples of CRC patients was successfully obtained in all cases. Presence of the KRAS G12D mutation was determined by pyrosequencing of FFPE tissue as a reference standard. Results of KRAS G12D mutation detection in FFPE tumors using ddPCR were in total agreement with pyrosequencing analysis. This was expected, given the fact that ddPCR has been proven to achieve higher sensitivity than pyrosequencing[49]. Once the KRAS G12D mutation had been screened in tumor tissues, DNA from stool samples obtained from the same patients prior to surgery was also analyzed. Thus, we were able to detect the KRAS G12D mutation in 8 out of 10 stool samples from patients known to carry this mutation in their tumors using both methods. It is noteworthy that 6 of these 8 samples were from early-stage patients (I-IIA), highlighting the potential of this approach to identify KRAS mutations at the initial stages of the disease.

Absorbance at a wavelength of 230 nm has been reported as an indicator of the level of potential PCR inhibitors in fecal samples[50], and it should be noted that the two negative samples showed peak of absorbance at this same wavelength. Thus, the sensitivity of detection in our assay could have been greatly reduced by the presence of PCR inhibitors in these samples.

The sample from Patient 17 is noteworthy for its remarkably high concentration of both mutated and WT copies. It is worth mentioning that this patient was subjected to cathartic preparation prior to sample collection due to an oversight. The rest of the samples were collected without any bowel preparation. We hypothesize that purging could have increased the exfoliation of tumor cells into the bowel lumen. This unexpected observation raises the question of whether bowel preparation could be advisable prior to sample collection to increase the sensitivity of detection in stool screening of KRAS mutations by ddPCR.

To our knowledge, this is the first study to evaluate the feasibility of detection of the KRAS G12D mutation in stool DNA from CRC patients using this particular ddPCR platform. Our results are in line with the above-mentioned recently published study by Herring et al[17], reporting the detection and accurate quantification of an mRNA biomarker in stool from CRC patients using the same ddPCR system. In light of these results, the analysis of CRC biomarkers in stool using ddPCR merits further study in larger cohorts of patients to evaluate the clinical utility of this approach.

We analyzed only the most prevalent KRAS mutation (G12D) in our population, as it was the only one with a sufficient number of samples available for analysis (n = 10). Another reason for choosing G12D as a target was that it has the highest incidence in CRC patients worldwide and is associated with poor clinical outcome[8,23]. For lower-incidence mutations, such as G12V, there were too few samples in our study population to provide conclusive results. The analysis of KRAS G12D performed in this study represents a proof-of-concept of the feasibility of this strategy as a first step prior to the screening of other relevant hotspot mutations.

This preliminary study demonstrates the capability of ddPCR to detect KRAS mutations in stool-derived DNA, acting as a complementary approach to tissue biopsy for tumor genotyping. These results pave the way for the ddPCR analysis of other molecular biomarkers of CRC in stool, including other KRAS, NRAS and BRAF mutations. A multiplex assay simultaneously covering all KRAS mutations relevant for anti-EGFR therapy decision-making would maximize the benefits and optimize the cost-effectiveness of this approach. Further studies involving larger cohorts of patients and samples collected at different time points throughout the progression of the disease should be performed in order to confirm the prognostic value and economic viability of this tool before implementation in clinical practice.

This study is the first to describe the detection of KRAS G12D mutation in stool-derived DNA from CRC patients using a commercially available ddPCR platform, including individuals at early stages of the disease. We hypothesized that ddPCR could be a reliable and sensitive method to analyze KRAS mutations in stool-derived DNA providing reproducible and accurate results. Our findings suggest this approach, which is fast, simple and affordable, could be adaptable to the detection of other clinically relevant molecular biomarkers for CRC management. These advantages with respect to other previously described stool-based strategies, together with instrumentation and protocols easily adoptable by any lab, make our approach more feasible for implementation into routine clinical practice. In light of our results, it could be proposed that biomarker analysis by ddPCR of stool samples may complement current CRC screening methods; stool-derived nucleic acid testing by ddPCR offers an alternative tool to tissue genotyping and blood-based biomarker quantification, being less invasive than the former and, probably, more time-sensitive than the later, especially at early stages, as tumor DNA will reasonably reach the fecal content more quickly than the bloodstream, at least during the initial phases of cancer development.

ARTICLE HIGHLIGHTS
Research background

Clinical management of colorectal cancer (CRC) requires analysis of molecular biomarkers, such as KRAS or NRAS mutations, which are associated with the emergence of resistance to therapy with biological agents. Tumor genotyping is usually performed using DNA from tissue biopsies, and, in recent years, from blood as well. However, at early disease stages, levels of mutated copies in circulating cell-free DNA may be, in some cases, too low for detection. Thus, extremely sensitive and non-invasive alternative methods are still needed to improve detection and achieve accurate quantification of these biomarkers.

Research motivation

Stool is an alternative and non-invasive source of genetic material for tumor genotyping in CRC. To date, several strategies based on analysis of molecular markers in fecal samples have been proposed, though their application in clinical practice remains limited due to their elevated cost and reduced sensitivity at early stages of disease.

Research objectives

The aim of this study was to assess the potential of droplet digital PCR (ddPCR) to detect the KRAS G12D mutation in stool-derived DNA from CRC patients as a proof-of-concept for the applicability of this technology as a non-invasive method of studying clinically relevant DNA biomarkers in stool.

Research methods

KRAS mutations were determined by pyrosequencing in DNA obtained from formalin-fixed paraffin-embedded (FFPE) tumor tissues. Then, KRAS G12D mutation was analyzed by ddPCR in FFPE tumors and stool-derived DNA in samples obtained from patients carrying this point mutation.

Research results

The KRAS G12D mutation was detected by ddPCR in FFPE tumor-derived DNA and in stool-derived DNA in 80% of all fecal samples from CRC patients with this mutation.

Research conclusions

This is the first study to describe the detection of the KRAS G12D mutation in stool-derived DNA from CRC patients using a commercially available ddPCR platform, including in individuals with early stages of the disease. dPCR served as a reliable tool for detecting this clinically relevant mutation in stool-derived DNA from CRC patients. Several stool-based strategies involving digital PCR have been investigated to analyze relevant mutations for CRC management. However, none of these approaches has been further developed and subjected to clinical validation for stool DNA screening to date.

The advantages of ddPCR technology, together with instrumentation and protocols easily adoptable by any lab, support a potential translation of this approach to clinical scenarios. Our results show that KRAS G12D detection in stool-derived DNA from CRC patients by ddPCR is feasible and suggests this technology might be useful for the analysis of other molecular markers in stool. The authors hypothesized that ddPCR could be a reliable and sensitive method of analyzing KRAS mutations in stool-derived DNA, providing reproducible and accurate results.

This study proposed a new strategy based on detecting KRAS mutations in stool-derived DNA using a commercially available ddPCR platform. ddPCR is an emulsion-based amplification technology with fluorescently labelled probes. KRAS G12D mutation detection in stool-derived DNA by ddPCR is a fast, simple, and affordable approach which could be adapted to detect other clinically relevant molecular biomarkers for CRC management. This technique is more feasible for implementation into routine clinical practice than other previously described stool-based strategies.

ddPCR provided sensitive, accurate, and reproducible results for detection of the KRAS G12D mutation in stool-derived DNA from CRC patients, especially at early stages of the disease. In light of our results, it could be proposed that biomarker analysis by ddPCR in stool samples may complement current CRC screening methods; stool-derived nucleic acid testing by ddPCR offers an alternative to tissue genotyping and blood-based biomarker quantification, is a less invasive tool than the former and is likely more time-sensitive than the latter, especially at early stages, as tumor DNA will reasonably reach the fecal content more quickly than the bloodstream, at least during the initial phases of cancer development.

Research perspectives

KRAS mutations are analyzable by ddPCR in stool-derived DNA from CRC patients, including early-stage patients. This observation merits further studies aimed at evaluating and improving the efficiency of this approach prior to its clinical application. These results pave the way for ddPCR analysis of other molecular biomarkers of CRC in stool. Further studies involving larger cohorts of patients and samples collected at different time points throughout the progression of the disease should be performed in order to confirm the prognostic value and economic viability of this tool before implementation in clinical practice. A multiplex assay simultaneously covering all KRAS mutations relevant for anti-EGFR-therapy decision-making would maximize the benefits and optimize the cost-effectiveness of this approach. This strategy should be further investigated as a complementary screening test for early detection of CRC.

ACKNOWLEDGMENTS

The authors would like to acknowledge Dr. Federico Rojo from the Department of Pathology at Fundación Jiménez Díaz University Hospital for his collaboration in this study. The authors also acknowledge Yolanda López Revuelta and all the Nursing staff from the Department of Surgery at Fundación Jiménez Díaz University Hospital for collaborating in sample collection. The authors also acknowledge Dr. Ignacio Mahíllo for statistical analysis and Oliver Shaw for his revision of the text for aspects related to the English language.

Footnotes

Manuscript source: Invited manuscript

Specialty type: Gastroenterology and hepatology

Country of origin: Spain

Peer-review report classification

Grade A (Excellent): 0

Grade B (Very good): B

Grade C (Good): 0

Grade D (Fair): 0

Grade E (Poor): 0

P- Reviewer: Gazouli M S- Editor: Ma YJ L- Editor: Filipodia E- Editor: Huang Y

References
1.  Stewart BW, Wild CP.  International Agency for Research on Cancer. World Cancer Report 2014. 1 edition. Lyon, France: World Health Organization 2014; .  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Peeters M, Price T. Biologic therapies in the metastatic colorectal cancer treatment continuum--applying current evidence to clinical practice. Cancer Treat Rev. 2012;38:397-406.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 60]  [Cited by in F6Publishing: 64]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
3.  European Medicines Agency. Erbitux: EPAR - Product Information Last updated on 03/02/2015. [Internet]. [cited 2017 Jun 15].  Available from: http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000558/WC500029119.pdf.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  European Medicines Agency. Vectibix: EPAR - Product Information Last updated on 09/03/2017 [Internet]. [cited 2017 Jun 15].  Available from: http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000741/WC500047710.pdf.  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Song QB, Wang Q, Hu WG. Anti-epidermal growth factor receptor monoclonal antibodies in metastatic colorectal cancer: a meta-analysis. World J Gastroenterol. 2015;21:4365-4372.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 0.7]  [Reference Citation Analysis (0)]
6.  Boleij A, Tack V, Taylor A, Kafatos G, Jenkins-Anderson S, Tembuyser L, Dequeker E, van Krieken JH. RAS testing practices and RAS mutation prevalence among patients with metastatic colorectal cancer: results from a Europe-wide survey of pathology centres. BMC Cancer. 2016;16:825.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 24]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
7.  Neumann J, Zeindl-Eberhart E, Kirchner T, Jung A. Frequency and type of KRAS mutations in routine diagnostic analysis of metastatic colorectal cancer. Pathol Res Pract. 2009;205:858-862.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 218]  [Cited by in F6Publishing: 236]  [Article Influence: 15.7]  [Reference Citation Analysis (0)]
8.  Zocche DM, Ramirez C, Fontao FM, Costa LD, Redal MA. Global impact of KRAS mutation patterns in FOLFOX treated metastatic colorectal cancer. Front Genet. 2015;6:116.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 13]  [Cited by in F6Publishing: 21]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
9.  Modest DP, Ricard I, Heinemann V, Hegewisch-Becker S, Schmiegel W, Porschen R, Stintzing S, Graeven U, Arnold D, von Weikersthal LF. Outcome according to KRAS-, NRAS- and BRAF-mutation as well as KRAS mutation variants: pooled analysis of five randomized trials in metastatic colorectal cancer by the AIO colorectal cancer study group. Ann Oncol. 2016;27:1746-1753.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 130]  [Cited by in F6Publishing: 187]  [Article Influence: 23.4]  [Reference Citation Analysis (0)]
10.  Lièvre A, Bachet JB, Le Corre D, Boige V, Landi B, Emile JF, Côté JF, Tomasic G, Penna C, Ducreux M. KRAS mutation status is predictive of response to cetuximab therapy in colorectal cancer. Cancer Res. 2006;66:3992-3995.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1669]  [Cited by in F6Publishing: 1661]  [Article Influence: 92.3]  [Reference Citation Analysis (0)]
11.  Amado RG, Wolf M, Peeters M, Van Cutsem E, Siena S, Freeman DJ, Juan T, Sikorski R, Suggs S, Radinsky R. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J Clin Oncol. 2008;26:1626-1634.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2390]  [Cited by in F6Publishing: 2348]  [Article Influence: 146.8]  [Reference Citation Analysis (0)]
12.  Andreatos N, Ronnekleiv-Kelly S, Margonis GA, Sasaki K, Gani F, Amini N, Wilson A, Pawlik TM. From bench to bedside: Clinical implications of KRAS status in patients with colorectal liver metastasis. Surg Oncol. 2016;25:332-338.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 20]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
13.  Jones RP, Sutton PA, Evans JP, Clifford R, McAvoy A, Lewis J, Rousseau A, Mountford R, McWhirter D, Malik HZ. Specific mutations in KRAS codon 12 are associated with worse overall survival in patients with advanced and recurrent colorectal cancer. Br J Cancer. 2017;116:923-929.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 67]  [Cited by in F6Publishing: 99]  [Article Influence: 14.1]  [Reference Citation Analysis (0)]
14.  Laurent-Puig P, Pekin D, Normand C, Kotsopoulos SK, Nizard P, Perez-Toralla K, Rowell R, Olson J, Srinivasan P, Le Corre D. Clinical relevance of KRAS-mutated subclones detected with picodroplet digital PCR in advanced colorectal cancer treated with anti-EGFR therapy. Clin Cancer Res. 2015;21:1087-1097.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 122]  [Cited by in F6Publishing: 132]  [Article Influence: 13.2]  [Reference Citation Analysis (0)]
15.  Diaz LA Jr, Williams RT, Wu J, Kinde I, Hecht JR, Berlin J, Allen B, Bozic I, Reiter JG, Nowak MA, Kinzler KW, Oliner KS, Vogelstein B. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature. 2012;486:537-540.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1259]  [Cited by in F6Publishing: 1301]  [Article Influence: 108.4]  [Reference Citation Analysis (0)]
16.  Olmedillas-López S, García-Arranz M, García-Olmo D. Current and Emerging Applications of Droplet Digital PCR in Oncology. Mol Diagn Ther. 2017; Epub ahead of print.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 115]  [Cited by in F6Publishing: 92]  [Article Influence: 13.1]  [Reference Citation Analysis (0)]
17.  Herring E, Kanaoka S, Tremblay É, Beaulieu JF. Droplet digital PCR for quantification of ITGA6 in a stool mRNA assay for the detection of colorectal cancers. World J Gastroenterol. 2017;23:2891-2898.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 14]  [Cited by in F6Publishing: 15]  [Article Influence: 2.1]  [Reference Citation Analysis (0)]
18.  Vogelstein B, Kinzler KW. Digital PCR. Proc Natl Acad Sci U S A. 1999;96:9236-9241.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Huggett JF, Foy CA, Benes V, Emslie K, Garson JA, Haynes R, Hellemans J, Kubista M, Mueller RD, Nolan T. The digital MIQE guidelines: Minimum Information for Publication of Quantitative Digital PCR Experiments. Clin Chem. 2013;59:892-902.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 575]  [Cited by in F6Publishing: 591]  [Article Influence: 53.7]  [Reference Citation Analysis (0)]
20.  Olmedillas López S, García-Olmo DC, García-Arranz M, Guadalajara H, Pastor C, García-Olmo D. KRAS G12V Mutation Detection by Droplet Digital PCR in Circulating Cell-Free DNA of Colorectal Cancer Patients. Int J Mol Sci. 2016;17:484.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 32]  [Cited by in F6Publishing: 37]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
21.  Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, Bartlett BR, Wang H, Luber B, Alani RM. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med. 2014;6:224ra24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2770]  [Cited by in F6Publishing: 3183]  [Article Influence: 318.3]  [Reference Citation Analysis (0)]
22.  Walther A, Johnstone E, Swanton C, Midgley R, Tomlinson I, Kerr D. Genetic prognostic and predictive markers in colorectal cancer. Nat Rev Cancer. 2009;9:489-499.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 496]  [Cited by in F6Publishing: 494]  [Article Influence: 32.9]  [Reference Citation Analysis (0)]
23.  Zlobec I, Kovac M, Erzberger P, Molinari F, Bihl MP, Rufle A, Foerster A, Frattini M, Terracciano L, Heinimann K. Combined analysis of specific KRAS mutation, BRAF and microsatellite instability identifies prognostic subgroups of sporadic and hereditary colorectal cancer. Int J Cancer. 2010;127:2569-2575.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 82]  [Cited by in F6Publishing: 87]  [Article Influence: 6.2]  [Reference Citation Analysis (0)]
24.  Lech G, Słotwiński R, Słodkowski M, Krasnodębski IW. Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances. World J Gastroenterol. 2016;22:1745-1755.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 234]  [Cited by in F6Publishing: 250]  [Article Influence: 31.3]  [Reference Citation Analysis (7)]
25.  Lyberopoulou A, Aravantinos G, Efstathopoulos EP, Nikiteas N, Bouziotis P, Isaakidou A, Papalois A, Marinos E, Gazouli M. Mutational analysis of circulating tumor cells from colorectal cancer patients and correlation with primary tumor tissue. PLoS One. 2015;10:e0123902.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 30]  [Cited by in F6Publishing: 34]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
26.  Galanopoulos M, Papanikolaou IS, Zografos E, Viazis N, Papatheodoridis G, Karamanolis D, Marinos E, Mantzaris GJ, Gazouli M. Comparative Study of Mutations in Single Nucleotide Polymorphism Loci of KRAS and BRAF Genes in Patients Who Underwent Screening Colonoscopy, With and Without Premalignant Intestinal Polyps. Anticancer Res. 2017;37:651-657.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11]  [Cited by in F6Publishing: 13]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
27.  Diehl F, Schmidt K, Durkee KH, Moore KJ, Goodman SN, Shuber AP, Kinzler KW, Vogelstein B. Analysis of mutations in DNA isolated from plasma and stool of colorectal cancer patients. Gastroenterology. 2008;135:489-498.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 166]  [Cited by in F6Publishing: 168]  [Article Influence: 10.5]  [Reference Citation Analysis (0)]
28.  Azuara D, Ginesta MM, Gausachs M, Rodriguez-Moranta F, Fabregat J, Busquets J, Pelaez N, Boadas J, Galter S, Moreno V. Nanofluidic digital PCR for KRAS mutation detection and quantification in gastrointestinal cancer. Clin Chem. 2012;58:1332-1341.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 44]  [Cited by in F6Publishing: 46]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
29.  Chang YS, Er TK, Lu HC, Yeh KT, Chang JG. Detection of KRAS codon 12 and 13 mutations by mutant-enriched PCR assay. Clin Chim Acta. 2014;436:169-175.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 9]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
30.  Oxnard GR, Paweletz CP, Kuang Y, Mach SL, O’Connell A, Messineo MM, Luke JJ, Butaney M, Kirschmeier P, Jackman DM. Noninvasive detection of response and resistance in EGFR-mutant lung cancer using quantitative next-generation genotyping of cell-free plasma DNA. Clin Cancer Res. 2014;20:1698-1705.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 570]  [Cited by in F6Publishing: 613]  [Article Influence: 61.3]  [Reference Citation Analysis (0)]
31.  Janku F, Angenendt P, Tsimberidou AM, Fu S, Naing A, Falchook GS, Hong DS, Holley VR, Cabrilo G, Wheler JJ. Actionable mutations in plasma cell-free DNA in patients with advanced cancers referred for experimental targeted therapies. Oncotarget. 2015;6:12809-12821.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 66]  [Cited by in F6Publishing: 79]  [Article Influence: 9.9]  [Reference Citation Analysis (0)]
32.  Tabernero J, Lenz HJ, Siena S, Sobrero A, Falcone A, Ychou M, Humblet Y, Bouché O, Mineur L, Barone C. Analysis of circulating DNA and protein biomarkers to predict the clinical activity of regorafenib and assess prognosis in patients with metastatic colorectal cancer: a retrospective, exploratory analysis of the CORRECT trial. Lancet Oncol. 2015;16:937-948.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 242]  [Cited by in F6Publishing: 244]  [Article Influence: 27.1]  [Reference Citation Analysis (0)]
33.  Zhang Y, Suehiro Y, Shindo Y, Sakai K, Hazama S, Higaki S, Sakaida I, Oka M, Yamasaki T. Long-fragment DNA as a potential marker for stool-based detection of colorectal cancer. Oncol Lett. 2015;9:454-458.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 4]  [Article Influence: 0.4]  [Reference Citation Analysis (0)]
34.  Davies RJ, Miller R, Coleman N. Colorectal cancer screening: prospects for molecular stool analysis. Nat Rev Cancer. 2005;5:199-209.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 136]  [Cited by in F6Publishing: 149]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
35.  Armengol G, Sarhadi VK, Ghanbari R, Doghaei-Moghaddam M, Ansari R, Sotoudeh M, Puolakkainen P, Kokkola A, Malekzadeh R, Knuutila S. Driver Gene Mutations in Stools of Colorectal Carcinoma Patients Detected by Targeted Next-Generation Sequencing. J Mol Diagn. 2016;18:471-479.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 7]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
36.  Loktionov A, O’Neill IK, Silvester KR, Cummings JH, Middleton SJ, Miller R. Quantitation of DNA from exfoliated colonocytes isolated from human stool surface as a novel noninvasive screening test for colorectal cancer. Clin Cancer Res. 1998;4:337-342.  [PubMed]  [DOI]  [Cited in This Article: ]
37.  Ahlquist DA, Harrington JJ, Burgart LJ, Roche PC. Morphometric analysis of the “mucocellular layer” overlying colorectal cancer and normal mucosa: relevance to exfoliation and stool screening. Hum Pathol. 2000;31:51-57.  [PubMed]  [DOI]  [Cited in This Article: ]
38.  Dhaliwal A, Vlachostergios PJ, Oikonomou KG, Moshenyat Y. Fecal DNA testing for colorectal cancer screening: Molecular targets and perspectives. World J Gastrointest Oncol. 2015;7:178-183.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 16]  [Cited by in F6Publishing: 24]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
39.  Ahlquist DA, Skoletsky JE, Boynton KA, Harrington JJ, Mahoney DW, Pierceall WE, Thibodeau SN, Shuber AP. Colorectal cancer screening by detection of altered human DNA in stool: feasibility of a multitarget assay panel. Gastroenterology. 2000;119:1219-1227.  [PubMed]  [DOI]  [Cited in This Article: ]
40.  Lidgard GP, Domanico MJ, Bruinsma JJ, Light J, Gagrat ZD, Oldham-Haltom RL, Fourrier KD, Allawi H, Yab TC, Taylor WR. Clinical performance of an automated stool DNA assay for detection of colorectal neoplasia. Clin Gastroenterol Hepatol. 2013;11:1313-1318.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 99]  [Cited by in F6Publishing: 108]  [Article Influence: 9.8]  [Reference Citation Analysis (1)]
41.  Heigh RI, Yab TC, Taylor WR, Hussain FT, Smyrk TC, Mahoney DW, Domanico MJ, Berger BM, Lidgard GP, Ahlquist DA. Detection of colorectal serrated polyps by stool DNA testing: comparison with fecal immunochemical testing for occult blood (FIT). PLoS One. 2014;9:e85659.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 53]  [Cited by in F6Publishing: 59]  [Article Influence: 5.9]  [Reference Citation Analysis (0)]
42.  Imperiale TF, Ransohoff DF, Itzkowitz SH. Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med. 2014;371:187-188.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 44]  [Cited by in F6Publishing: 97]  [Article Influence: 9.7]  [Reference Citation Analysis (0)]
43.  Onieva-García MÁ, Llanos-Méndez A, Baños-Álvarez E, Isabel-Gómez R. A systematic review of the clinical validity of the Cologuard™ genetic test for screening colorectal cancer. Rev Clin Esp. 2015;215:527-536.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 2]  [Article Influence: 0.2]  [Reference Citation Analysis (0)]
44.  Dong SM, Traverso G, Johnson C, Geng L, Favis R, Boynton K, Hibi K, Goodman SN, D’Allessio M, Paty P. Detecting colorectal cancer in stool with the use of multiple genetic targets. J Natl Cancer Inst. 2001;93:858-865.  [PubMed]  [DOI]  [Cited in This Article: ]
45.  Zou H, Taylor WR, Harrington JJ, Hussain FT, Cao X, Loprinzi CL, Levine TR, Rex DK, Ahnen D, Knigge KL. High detection rates of colorectal neoplasia by stool DNA testing with a novel digital melt curve assay. Gastroenterology. 2009;136:459-470.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 76]  [Cited by in F6Publishing: 81]  [Article Influence: 5.4]  [Reference Citation Analysis (0)]
46.  Qi Z, Ma Y, Deng L, Wu H, Zhou G, Kajiyama T, Kambara H. Digital analysis of the expression levels of multiple colorectal cancer-related genes by multiplexed digital-PCR coupled with hydrogel bead-array. Analyst. 2011;136:2252-2259.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 12]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
47.  Deng L, Qi Z, Zou B, Wu H, Huang H, Kajiyama T, Kambara H, Zhou G. Digital detection of multiple minority mutants in stool DNA for noninvasive colorectal cancer diagnosis. Anal Chem. 2012;84:5645-5652.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 10]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
48.  Huang H, Li S, Sun L, Zhou G. Digital detection of multiple minority mutants and expression levels of multiple colorectal cancer-related genes using digital-PCR coupled with bead-array. PLoS One. 2015;10:e0123420.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 1]  [Article Influence: 0.1]  [Reference Citation Analysis (0)]
49.  Mukaide M, Sugiyama M, Korenaga M, Murata K, Kanto T, Masaki N, Mizokami M. High-throughput and sensitive next-generation droplet digital PCR assay for the quantitation of the hepatitis C virus mutation at core amino acid 70. J Virol Methods. 2014;207:169-177.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 20]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
50.  Iker BC, Bright KR, Pepper IL, Gerba CP, Kitajima M. Evaluation of commercial kits for the extraction and purification of viral nucleic acids from environmental and fecal samples. J Virol Methods. 2013;191:24-30.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 43]  [Article Influence: 3.9]  [Reference Citation Analysis (0)]