Ilhame Ben Larbi

Electronic nose can discriminate colorectal carcinoma and advanced adenomas by fecal volatile biomarker analysis: proof of principle study

In the course and prognosis of colorectal cancer (CRC), early detection and treatment are essential factors. Fecal immunochemical tests (FITs) are currently the most commonly used non‐invasive screening tests for CRC and premalignant (advanced) adenomas, however, with restricted sensitivity. We hypothesized that fecal volatile organic compounds (VOCs) may serve as a diagnostic biomarker of CRC and adenomas. In this proof of concept study, we aimed to assess disease‐specific VOC smellprints in fecal gas to distinguish patients with CRC and advanced adenomas from healthy controls. Fecal samples of patients who were scheduled to undergo an elective colonoscopy were collected. An electronic nose (Cyranose 320®) was used to measure VOC patterns in fecal gas from patients with histopathologically proven CRC, with advanced adenomas and from controls (no abnormalities seen at colonoscopy). Receiver operator characteristic curves and corresponding sensitivity and specificity for detection of CRC and advanced adenomas were calculated. A total of 157 stool samples (40 patients with CRC, 60 patients with advanced adenomas, and 57 healthy controls) were analyzed by electronic nose. Fecal VOC profiles of patients with CRC differed significantly from controls (area under curve ± 95%CI, p‐value, sensitivity, specificity; 0.92 ± 0.03, <0.001, 85%, 87%). Also VOC profiles of patients with advanced adenomas could be discriminated from controls (0.79 ± 0.04, <0.001, 62%, 86%). The results of this proof of concept study suggest that fecal gas analysis by an electronic nose seems to hold promise as a novel screening tool for the (early) detection of advanced neoplasia and CRC.

Novel stool-based protein biomarkers for improved colorectal cancer screening : a case-control study

Screening aims to lower the burden of colorectal cancer (CRC) by either preventing cancer from developing or detecting it at a curable stage (1). Although colonoscopy remains the gold standard for detecting colorectal tumors, for reasons of compliance and cost, most population-wide screening programs use noninvasive stool-based tests for triage to colonoscopy (2). The guaiac-based fecal occult blood test has been proven to reduce mortality from CRC (35). The newer fecal immunochemical test (FIT), which uses an antibody against human hemoglobin, outperforms the guaiac-based fecal occult blood test and is now used widely (69). Yet, the sensitivity of FIT for detecting CRC is suboptimal (79%) and even poorer (31%) for finding advanced colonic adenomas, precursor lesions with an increased risk for progression (10, 11). Molecular screening tests have the potential to detect colorectal tumors better than FIT (12, 13). Indeed, multitarget stool DNA testing combined with FIT has been shown to have a higher sensitivity than FIT alone (14), but it is too costly to implement in population-wide screening programs. In contrast, like hemoglobin in FIT, protein biomarkers can be translated into simple and cost-effective antibody-based screening tests (15). Ideally, these biomarkers also could be quantified in the small stool sample volumes used in FIT-based screening programs. However, thus far, alternative protein biomarkers have failed to improve current hemoglobin-based CRC stool-screening tests (12). Technologic advancements in mass spectrometry now allow for in-depth proteomics for biomarker discovery in complex biological samples (16, 17). A classic approach is to first identify discriminating markers in tissue or cell-line material and then validate them in the final analyte, such as stool. However, constituents of the analyte ultimately used for screeningsuch as bacterial proteases and glycosidases in stoolmay affect test performance, possibly leading to validation failure (12, 18). Therefore, discovering biomarkers directly in the biological sample taken for screening, namely stool, may be a powerful alternative. In the present study, we set out to identify proteins in stool that outperform or complement fecal hemoglobin as a biomarker for early detection of CRC and advanced adenomas. Methods A brief overview of the methods is given here; full sample details and methods are provided in Supplements 1 and 2. For an overview of the workflow, see Figure 1 of Supplement 1. Supplement 1. Supplementary Appendix Supplement 2. Supplementary Tables Sample Series Written informed consent was obtained from all persons who provided stool samples. The study was conducted in compliance with institutional ethical regulations. See the Appendix Table for clinicopathologic characteristics. Appendix Table. Clinicopathologic Characteristics of Stool Sample Series 1 and 2 Sample Series 1 Twenty-two stool subsamples (12 from patients with CRC and 10 from persons without colorectal neoplasia) were collected from a colonoscopy-controlled referral population at VU University Medical Center in Amsterdam, the Netherlands, between 2003 and 2006. Sample Series 2 Whole stool samples from 293 persons with CRC (n= 81), with advanced adenomas (n= 40), with nonadvanced adenomas (n= 43), or without colorectal neoplasia (n= 129) were collected from a colonoscopy-controlled referral population at several centers in the Netherlands and Germany between 2005 and 2012. Sample Series 3 Fecal immunochemical test samples from 72 persons with CRC (n= 14), advanced adenoma (n= 16), or nonadvanced adenoma (n= 18) or who did not have colorectal neoplasia (n= 24) from a colonoscopy-controlled referral population at Kennemer Gasthuis Hospital in Haarlem, the Netherlands, between 2012 and 2014. Proteomics Analysis With Nanoscale Liquid Chromatography Coupled to Tandem Mass Spectrometry Proteins were extracted from stool as described previously (19), with a few adaptations. Equal amounts of protein were run through sodium dodecyl sulfate polyacrylamide gel electrophoresis (Invitrogen) and processed further by in-gel tryptic digestion (20). Peptides were separated by nanoscale liquid chromatography and detected on an LTQ-FT hybrid mass spectrometer (Thermo Fisher) (sample series 1) or a Q Exactive mass spectrometer (Thermo Fisher) (sample series 2). Data acquisition was not successful for 2 CRC samples in series 2. Spectra obtained from tandem mass spectrometry were searched against the UniProt human reference proteome FASTA file, release January 2014, by using MaxQuant 1.4.1.2 (21). Protein abundance was quantified by label-free spectral counting (22). Antibody-Based Assays Fecal immunochemical test fluids from sample series 3 were analyzed by using antibody-based assays for myeloperoxidase (MPO), alpha-2-macroglobulin (A2M), retinol binding protein 4 (RBP4), and adiponectin and analyzed with Discovery Workbench 4.0 software (Meso Scale Diagnostics). Statistical Analysis Statistical analyses were performed in the R computing environment, version 3.1.1 (The R Foundation), including the packages rpart, pROC, gplots, and ggplot2 (2326). Spectral counts were subjected to global normalization (27). Hierarchical clustering was performed on log2 (normalized expression values plus 1) by using the Euclidean distance for sample clustering, the Spearman distance for protein clustering, and complete linkage in both. Heat maps show the Z scores for individual proteins. Univariate differential abundance analysis was performed by using the beta-binomial test (27). Proteins consistently more abundant in CRC than control samples in both series 1 and 2 (BenjaminiHochbergcorrected P value; Q 0.05) constituted input for selecting specific biomarker panels. Biomarker panels were defined by using 2 statistical methods on sample series 2, namely logistic regression (exhaustive search) and classification and regression tree (CART) analysis. Receiver-operating characteristic (ROC) analysis was used to evaluate the performance of protein panels in discriminating between samples with advanced adenoma or CRC and those without colorectal neoplasia. Areas under the curve (AUCs) from ROC curves were compared and evaluated for statistical difference by using the bootstrap method from the pROC package. To assess the statistical significance of the difference in sensitivity between any marker panel and hemoglobin at 95% specificity, the McNemar test was used. Spearman rank correlation, MannWhitney, or KruskalWallis tests were used to assess the relation between protein abundancy and tumor characteristics, such as size, location, stage (CRC), histology (advanced adenoma), and grade of dysplasia (advanced adenoma). Role of the Funding Source The funding sources had no role in the design, conduct, or reporting of the study or in the decision to submit the manuscript for publication. Results Proteomics Analysis of Human Stool Samples A total of 468 human proteins were identified in sample series 1 (Table 1 of Supplement 2 and Figure 2 of Supplement 1). Spectral counts for the alpha and beta chains of hemoglobin, known to be present in equal amounts (28), showed a strong correlation (= 0.95, P < 0.001) (Figure 3A of Supplement 1). Likewise, the S100 calcium binding protein A8 and A9 (S100A8 and S100A9) calprotectin subunits were strongly correlated (= 0.91, P < 0.001) (Figure 3B of Supplement 1). Unsupervised cluster analysis revealed that the protein profile of most CRC stool samples differed from that of control samples (Appendix Figure, A). Because these results confirm the feasibility of quantifying CRC-specific human proteins in stool samples, the analysis was extended to the second, larger series of samples. Appendix Figure. Unsupervised hierarchical cluster analysis of human protein levels in stool samples. Shown are clusters and heat maps for sample series 1 (A) and 2 (B). The bluered color scale of the heat maps depicts protein levels as measured in spectral counts (blue: low; red: high). Green- and red-coded samples in the legend bar represent control and CRC stool samples, respectively. CRC = colorectal cancer. Subsequent analysis of 291 stool samples (Appendix Table) revealed a total of 733 human proteins (Table 2 of Supplement 2 and Figure 2B of Supplement 1) and reidentified 78% of the proteins (367 of 468) from sample series 1. Also in this second sample series, protein levels of hemoglobin alpha and beta, as well as the calprotectin subunits, were highly correlated (= 0.94, P < 0.001, and = 0.8, P < 0.001, respectively) (Figure 3C and 3D of Supplement 1). Again, the CRC stool samples had a protein profile different from that of the control samples (Appendix Figure, B). In sample series 1 and 2, a total of 834 human proteins were detected, 367 (44%) of which were common to both series (Table 3 of Supplement 2 and Figure 2C of Supplement 1). Proteins Discriminating CRC From Control Samples Signals that arise during tumor development are most suitable as biomarkers. Therefore, most cancer screening tests are based on positive signals, so we focused on proteins that were more abundant in the CRC than the control samples. Differential abundance analysis (CRC vs. control samples; fold change >0, P 0.05) yielded 93 and 213 proteins in sample series 1 and 2, respectively, with 55 proteins common to both (Table 3 of Supplement 2). This list of 55 proteins decreased to 29 after correction for multiple testing (that is, Q 0.05) (Table). These 29 proteins included hemoglobin subunits alpha 1, beta, and delta (HBA1, HBB, and HBD). Because population-based screening requires high sensitivity combined with high specificity, specificity was fixed at 95% to evaluate the corresponding sensitivities. At a specificity of 95%, 6 proteinscomplement C3 (C3), A2M, haptoglobin (HP), complement C5 (C5), fibronectin 1 (FN1), and ceruloplasmin (CP)had a statistically significantly higher sensitivity than HBA1 (Figure

S1123 Double Versus Single Sampling of Fecal Immunochemical Tests for Colorectal Cancer Screening; Added Value or Added Costs?

Background Fecal immunochemical tests (FITs) are state of the art in colorectal cancer(CRC) screening. Sensitivity of a single FIT for advanced neoplasia is around 50%. Theoretically, as blood loss from colon tumors can be intermittent, sensitivity of FITs could improve by double sampling. This study aims to compare the sensitivity of single FIT sampling and double FIT sampling at different cut-off values, for the detection of advanced neoplasia. Methods All subjects (≥18 years) scheduled for elective colonoscopy in three participating centers in the Amsterdam area were asked to perform FITs (OC sensor®) on two consecutive days. FIT results were compared with colonoscopy and histology as gold standard. Test performance of single FIT was compared to the sensitivity of double FIT sampling. Double FIT sampling was considered positive if one of both FITs was higher than the cut-off value. Test performances were evaluated at cut-off values ranging from 50-150ng/ml (incremental steps of 25ng/ml). Results Of 1105 subjects who performed two FITs and underwent total colonoscopy, 140 (9,4%) had advanced neoplasia (AN), of which 34 were CRC and 106 were advanced adenomas (AA). Of the CRC cases, 70% were Dukes stage A or B (stage unknown in 2). Positivity rates for single FIT ranged from 11-17%, and for double FIT from 14-23%. At the same cut-off value for positivity, sensitivity of double FIT sampling was higher than sensitivity of single FIT sampling. For any particular specificity (e.g. 90%), the sensitivity of double FIT was slightly higher than that of single FIT at a lower cut-off value (see table), but these differences were not statistically significant. Conclusions Two fold sampling of FIT does increase sensitivity for advanced neoplasia. However, at a given specificity, sensitivity of double sampling is comparable to single sampling at a lower cutoff value. Sensitivity and specificity of single and double FIT testing for the detection of advanced neoplasia

930 Comparing Three Different Strategies of Double Sampling by Fecal Immunochemical Tests for Detection of Advanced Colorectal Neoplasm's

Background Fecal Immunochemical Tests (FITs) are widely used for Colorectal Cancer (CRC) screening. Some sampling schemes use one-day FIT testing, whereas others use twoday FIT testing. Data on sensitivity and specificity of two-day FIT testing are lacking. This study aims to compare the difference in sensitivity and specificity of three different strategies of two-day FIT sampling, at different cut-off values. Methods In three hospitals in the Amsterdam area, all subjects ≥18 years who were referred for elective colonoscopy were asked to perform a FIT (OC sensor®) on two consecutive days. Colonoscopy and histology were considered as gold standard. Two-day FIT sampling was defined positive in three different ways: 1) when at least one of two FITs was above the cut-off value (FIT+), 2) when both FITs were above the cut-off value(FIT++), and 3) when the geometric mean of two FITs was above the cut-off value (FITmean). Test performance of all three strategies was evaluated at cut-off values of 50, 75 and 100ng/ml. Results In 1105 subjects with complete colonoscopy, 140 (9,4%) AN were found (34 CRCs and 106 advanced adenomas). Of the CRC cases, 70% were Dukes stage A or B (stage unknown in 2). Positivity rates for FIT+ ranged from 16-23%, for FIT++ from 10-13% and for FITmean from 13-17% (see table). At any cut-off level, FIT++ resulted in the lowest and FIT+ in the highest sensitivity. FIT++ showed a higher specificity than both other strategies (see table). Conclusions The most sensitive strategy in two-day FIT sampling is defining the test positive when at least one of both FITs passes the cut off (FIT+), whereas the highest specificity is obtained when both FITs need to be positive for calling the tests positive (FIT++). At all cut-off values, FITmean offers substantially better specificity than FIT+, while sensitivity is substantially higher than FIT++. Sensitivity and specificity of three methods to use two-day FIT sampling for the detection of advanced neoplasia

T2021 Higher Cut Off Values for Fit in CRC-Screening: Less Colonoscopies, Same Detection Rates for Curable Cancers

Introduction: The Fecal Immunochemical Test(FIT) is a next generation Faecal Occult Blood Test(FOBT)and has been proposed as screening tool for Colorectal Cancer(CRC). The goal of screening is to detect CRC in an early, curable stage(i.e. Dukes A+B). Some variants of FITs produce a quantitative outcome which allows for adjusting the threshold for calling a test positive. A higher cut off value will result in less positive tests and subsequently less screenees referred for colonoscopy and thus less strain on the endoscopic capacity. However it is unknown whether a higher cut off value will impair the detection rate of(curable)colorectal cancers. Aim: To assess the effect of a higher cut off value of a quantitative FIT on the positivity rate and on the detection rate of curable early stage CRCs. Methods: All patients aged ≥18 years and scheduled for a colonoscopy in 5 participating hospitals were asked to perform a FIT(OC sensor®, Eiken chemical Co, Japan) on one bowel movement the day prior to colonoscopy. Tests of all patients were assessed using cut-off values of 50, 100, 150 and 200 ng haemoglobin per ml. For analysis of all tests, the desktop analyser “OCSENSOR μ” was used. Test results were compared with the gold standard colonoscopy. Results: In 1,897 individuals, who underwent total colonoscopy, 62 cases of colorectal cancer(3.3%) were identified. 28/62 patients were diagnosed with early stage (Dukes A+B) colorectal cancer and 31 patients with late stage(Dukes C+D). Three rectal cancers could not be accurately staged due to the effects of neo-adjuvant radiotherapy. In our total population of 1,897 individuals, the OC sensor® was positive in 8.8%, 9.8%, 11.4% and 14.0% at cut offs of 200, 150, 100, and 50 ng/ml, respectively. The detection rates for early stage CRCs ranged from 75.0% to 78.5% depending on the threshold of FIT(Table 1). Conclusions: A higher cut off value for FIT can reduce strain on colonoscopy capacity with only a slight decrease in detection rates of curable, early stage, colorectal cancers.