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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Ed. by Gillery, Philippe / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Payne, Deborah A. / Schlattmann, Peter / Tate, Jillian R.

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Volume 56, Issue 1

Issues

Cancer sniffer dogs: how can we translate this peculiarity in laboratory medicine? Results of a pilot study on gastrointestinal cancers

Concetta Panebianco
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Edgar Kelman / Kristel Vene
  • Competence Center of Food and Fermentation Technologies, Tallinn, Estonia
  • Department of Food Processing, Tallinn University of Technology, Tallinn, Estonia
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/ Domenica Gioffreda
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
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/ Francesca Tavano
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
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/ Raivo Vilu
  • Competence Center of Food and Fermentation Technologies, Tallinn, Estonia
  • Department of Chemistry, Tallinn University of Technology, Tallinn, Estonia
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/ Fulvia Terracciano
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
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  • De Gruyter OnlineGoogle Scholar
/ Illar Pata / Kaarel Adamberg
  • Competence Center of Food and Fermentation Technologies, Tallinn, Estonia
  • Department of Food Processing, Tallinn University of Technology, Tallinn, Estonia
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  • De Gruyter OnlineGoogle Scholar
/ Angelo Andriulli
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
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  • De Gruyter OnlineGoogle Scholar
/ Valerio Pazienza
  • Corresponding author
  • Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, San Giovanni Rotondo (FG), Italy
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Published Online: 2017-06-07 | DOI: https://doi.org/10.1515/cclm-2016-1158

Abstract

Background:

Identification of cancer biomarkers to allow early diagnosis is an urgent need for many types of tumors, whose prognosis strongly depends on the stage of the disease. Canine olfactory testing for detecting cancer is an emerging field of investigation. As an alternative, here we propose to use GC-Olfactometry (GC/O), which enables the speeding up of targeted biomarker identification and analysis. A pilot study was conducted in order to determine odor-active compounds in urine that discriminate patients with gastrointestinal cancers from control samples (healthy people).

Methods:

Headspace solid phase microextraction (HS-SPME)-GC/MS and GC-olfactometry (GC/O) analysis were performed on urine samples obtained from gastrointestinal cancer patients and healthy controls.

Results:

In total, 91 key odor-active compounds were found in the urine samples. Although no odor-active biomarkers present were found in cancer carrier’s urine, significant differences were discovered in the odor activities of 11 compounds in the urine of healthy and diseased people. Seven of above mentioned compounds were identified: thiophene, 2-methoxythiophene, dimethyl disulphide, 3-methyl-2-pentanone, 4-(or 5-)methyl-3-hexanone, 4-ethyl guaiacol and phenylacetic acid. The other four compounds remained unknown.

Conclusions:

GC/O has a big potential to identify compounds not detectable using untargeted GC/MS approach. This paves the way for further research aimed at improving and validating the performance of this technique so that the identified cancer-associated compounds may be introduced as biomarkers in clinical practice to support early cancer diagnosis.

Keywords: cancer sniffer dogs; gastrointestinal cancer; VOC

Introduction

Gastrointestinal (GI) cancers encompass malignancies affecting different organs and tracts of the digestive apparatus, which together account for around 40% of cancer-related deaths worldwide [1], [2], [3]. Among the GI cancers, colorectal cancer is the most frequent, with a prognosis highly dependent on the stage at diagnosis [2]. Also common is gastric cancer, which is the third most deadly tumor [1], [4], partly due to late diagnosis [5]. Indeed, early-stage disease is often curable, but usually it remains undiagnosed until late stage [1]. The GI cancer with the worst prognosis, however, is the pancreatic cancer, the fourth most lethal cancer worldwide, with mortality approaching incidence [6], [7]. This cancer owes its poor clinical outcome to late-stage detection, biological aggressiveness of the disease, and resistance to conventional therapies [6], [8]. It is therefore evident that for GI tumors early detection is essential to give patients the best chance of treatment effectiveness. Regrettably, early diagnosis is often difficult to achieve, since some screening tests may be expensive, ineffective in finding small tumors, or may even introduce additional health risks (e.g. exposure to radiations, biopsies and other invasive exams) [9]. Diagnosis of GI cancers is usually based on invasive endoscopic procedures [10], [11]. For these reasons, new and non-invasive detection methods endowed with sensitivity and specificity are needed. In recent decades great efforts have been devoted to discovering candidate biomarkers which could allow a non- invasive, cost-effective identification of the disease.

Recently, the analysis of volatile organic compounds (VOCs) as a diagnostic tool has attracted much attention [10], supported by the evidence that a specific profile of odorous compounds discriminating healthy and neoplastic people can be successfully sensed by the canine olfactory system [12], [13], [14]. Lippi and Cervellin [12] reviewed recent studies reporting that appropriately trained dogs (the so called “sniffer-dogs”) exhibit an extraordinary ability to detect various types of cancers by recognizing a distinctive “odor signature” in urine, sweat, breath and blood.

Despite its potential, canine olfactory detection of cancers in the clinical practice has some limitations: dogs have to be suitably trained and this is expensive and time-consuming [15]; the performance may be influenced by polymorphisms in the olfactory receptor gene and thus by the breed of dogs [13], [16]. Moreover, it is still unclear what dogs recognize in cancer samples [12], whether a single or rather a mix of odor-active compounds [14]. To address all these issues, the olfactory cancer detection by dogs should be substantiated with laboratory tests [12]. A well-established technique for detecting VOCs in biological fluids, which can be used in laboratory medicine, is represented by gas chromatography/mass spectrometry (GC/MS) [17]. An appealing alternative approach to this kind of study, which could help to shed light on the scientific bases of canine cancer detection, is represented by gas chromatography-olfactometry (GC/O), which couples the traditional GC separation with human olfactory detection in order to identify odor-active compounds within a mixture [18]. Each odorous compound eluted by GC is directed through an odor port to trained human assessors which can detect, measure and describe the quality of the odor [18], [19]. This technique allows traces of molecules with extremely low odor threshold (not visible by GC/MS, but with strong odor and therefore detectable by GC/O). To date, it has mainly been applied in the analysis of food and drink aromatic compounds and in the field of fragrances and perfumery, and its application in the medical field is only recently emerging as a promising tool to help diagnoses [18].

Comparing different biological samples, the urine has proven to contain a greater variety of VOCs [20], [21], reflecting the products of the overall body metabolism and its alterations [21]. Moreover, relatively large volumes of sample can be easily obtained [22]. VOC levels extracted from the headspace of urine have been investigated and found to discriminate healthy subjects from patients suffering from lung [21], [23], prostate [24], biliary [25] and renal cancer [26]. As for the GI cancers, VOCs have been determined in the urine of colorectal cancer patients [27] and in a pilot study on the urine of patients with biliary malignancy [25]. To the best of our knowledge, no previous analysis of VOCs in the urine of gastric and pancreatic cancer patients has been performed. Further, no application of GC/O in the medical field for the detection of potential cancer biomarkers has been reported. For this purpose, we performed for the first time a pilot study on urine samples from GI cancer-affected people (above all gastric and pancreatic ones) using Headspace solid phase microextraction (HS-SPME)-GC/MS and GC-Olfactometry (GC/O) analysis in order to discover one or more odor-active compounds differentiating cancer and cancer-free subjects that could be eligible as potential GI cancer biomarkers.

A deeper exploration of this area would be desirable since the identification of one or more chemical markers of disease would be of great impact in the development of diagnostic tests.

Materials and methods

Patient’s selection and sample’s preparation

Twenty-three patients with a confirmed diagnosis of gastrointestinal cancer, referred to our Gastroenterology Department of the “Casa Sollievo della Sofferenza” Hospital of San Giovanni Rotondo, Italy, and fifteen healthy donors (controls) were enrolled in the study. All patients signed an informed consent approved by the Local Ethics Committee. The consent included clinical-pathological patient’s features. The latter are reported in the Table 1. Urine from both patients and controls were collected and stored at −20°C until the analysis. For GC/O and GC/MS analysis, 2 mL of urine (defrosted to room temperature) was measured into 20 mL glass headspace vial with glass-covered magnetic stir-bar, 0.8 g of sodium chloride was added and pH was adjusted to 1–2 using hydrochloric acid (HCl:H2O 1:1) as suggested by Silva et al. [28]. Vials were capped with PTFE-silicon septa and placed in an autosampler tray at room temperature just before analysis. Samples were brought one-by-one into magnetic stirring chamber for volatile extraction. Pre-incubating time was 5 min and adsorption time was 45 min (250 rpm). Pre-incubation and adsorption temperatures were both 40°C. For SPME, 30/50 μm DVB/Car/PDMS Stableflex 2 cm long fiber from Supelco (Bellefonte, PA) was used. After extraction the fiber was injected to GC/MS-TOF, GC/qMS or GC/O for desorption (10 min).

Table 1:

Demographic and clinical features of patients and controls.

Chemicals and consumables

Sodium chloride, hydrochloric acid and alkane mix (C8-C22) were purchased from Sigma-Aldrich (Germany).

GC/O and GC/MS apparatus parameters

GC/O was equipped with odor detection port ODP3 (Gerstel, Germany). GC/MS-TOF (GCT Premier CAB021, Waters, UK) and GC/qMS (5975 Agilent Technologies, USA) were used to identify the compounds. The GC column for GC/MS-TOF and GC/O was DB5-MS, 30 m×0.25 mm×1.0 μm (Phenomenex, USA). For GC/qMS HP-5MS 30 m×0.25 mm×0.25 μm (Agilent Technologies) and ZB-Wax plus 30 m×0.25 mm×0.25 μm (Phenomenex, USA) was used. Both GC/qMS and GC/O inlets were Merlin Microseal (Agilent, USA) and GC/MS tof had PTV (CIS-4, Gerstel, Germany) inlet. All were run in splitless mode. A 0.75 mm i.d. liner at 250°C was used in all injectors. The carrier gas was He (5.0, AGA Estonia, Estonia) with a flow 1.0 mL/min in both GC/MS and 2.0 mL/min in GC/O. For the GC/MS identification ChromaLynx program (Waters, UK), Chemstation (Agilent Technologies, USA), NIST05 library, retention indices and odor qualities (Flavornet.org, Pherobase.com and Thegoodscentcompany.com) were used. Different oven programs were used for GC/MS-TOF, GC/qMS and GC/O analysis. For the GC/MS-TOF and GC/qMS HP-5MS column, the following program was used: starting at 45°C, 5°C/min to 280°C, holding time 3 min. Total run time was 50 min. For the GC/qMS ZB-Wax column, the program was 35°C, 10°C/min to 250°C (total run 21.5 min). The GC/O oven program was shorter to avoid assessor fatigue, starting at 35°C, 17°C/min to 280°C, holding time 4 min (total run time 17.41 min).

Data analysis

In GC/O analysis three trained assessors (two female, one male) were used to detect the odors and assess the intensities in a 5-point scale (1 – fairly detectable, 5 – extremely strong) and describe odor quality in one parallel [29]. GC/O data were processed using modified frequency formula:

MF(%)=F(%)*I(%)

where F(%) is the detection frequency expressed as percentage of maximum detection and I(%) is a sum of odor intensities of different assessors expressed as percentage of maximum sum of intensity. MF(%) shows the importance of the compound in a sample. Key odor-active compounds were identified as compounds with MF(%) value of at least 11.2%. Compounds with low MF(%) were not screened as compounds which may come from the environment (e.g. diet-derived) and are not specific to cancer metabolism.

Statistical analysis

Results are expressed as mean±SD. Comparisons were made using a Student’s t-test. Differences were considered as statistically significant when p < 0.05* or p < 0.01**.

Results

Comparative GC/O analysis of VOCs in urine samples of GI cancer patients and healthy controls

In total, 91 key odor-active compounds were found in the urine samples, whose retention indices, odor qualities and MF(%) are reported in Table 2.

Table 2:

Odor quality and odor activities of key odor compounds in healthy individuals and cancer carrier urine samples among three GC/O assessors.

According to GC/O data, no odor-active biomarkers present only in a cancer carrier’s urine were found. Despite this, significant differences were discovered in the odor activities of 11 compounds in the urine of healthy and diseased people (Table 3). Seven of above mentioned compounds were identified, and other four remained unknown. Among the identified compounds, the sulfur compounds were as follows: thiophene, 2-methoxythiophene and dimethyl disulphide; ketones: 3-methyl-2-pentanone, 4-(or 5-) methyl -3-hexanone; and aromatic compounds: 4-ethyl guaiacol and phenylacetic acid.

Table 3:

Odor activity of the compounds differentiating the urine samples of healthy and deseased people.

Average modified frequency values were calculated for the seven identified compounds that differentiate the urine of healthy and diseased people (Figure 1). Dimethyl disulphide, 2-methoxythiophene and phenylacetic acid odor activities were elevated in cancer carrier’s urine and thiophene, 3-methyl-2-pentanone, 4-(or 5-) methyl-3-hexanone, 4-ethyl guaiacol odor intesities were higher in the urine of healthy people.

Odor activity of identified compounds differentiating the urine of healthy controls and cancer carriers. Differences were considered as statistically significant when p<0.05 (*) or p<0.01 (**). The average of modified frequency (MF [%]) is calculated among the determinations of all three assessors on all healthy and diseased people urine samples.
Figure 1:

Odor activity of identified compounds differentiating the urine of healthy controls and cancer carriers.

Differences were considered as statistically significant when p<0.05 (*) or p<0.01 (**). The average of modified frequency (MF [%]) is calculated among the determinations of all three assessors on all healthy and diseased people urine samples.

GC/O method has a large variability due to the human factor. The results depend on the assessor’s physiological state: tiredness, breathing rhythm, genetic background etc. Thus, only significant differences in the odor activities of compounds were taken into account. Difference was defined as significant when odor activities between healthy and diseased people were differentiating two or more times in the same way, and that in case of at least two assessors. Although phenylacetic acid does not have drastic changes in MF(%) value, it was included in the list because assessor A2 detected it almost in all cancer samples with greater intensity than in controls. As for thiophene and 4-ethyl guaiacol, differences between healthy controls and cancer carriers proved statistically significant (Figure 1).

Confirmation of GC/O results by GC/MS

To ensure that the differences in odor activities are caused by actual differences in the content of certain compounds and not by occasional variability in MF(%) values, average peak areas on GC/MS chromatograms of above mentioned compounds were calculated (Figure 2). Peak areas indirectly represent the concentration of compounds in the sample. The average peak area is not shown for 4-(or 5-)methyl-3-hexanone as it was present in samples at trace levels.

The average GC/MS peak areas of the compounds differentiating the urine of healthy controls and cancer carriers. Differences were considered as statistically significant when p<0.05 (*) or p<0.01 (**). The average is calculated among all healthy and diseased people urine samples independently of detection of compound in a precise sample during GC/O analysis. Peak area of 2-methoxythiophene is referred to the only one control sample where it was detected.
Figure 2:

The average GC/MS peak areas of the compounds differentiating the urine of healthy controls and cancer carriers.

Differences were considered as statistically significant when p<0.05 (*) or p<0.01 (**). The average is calculated among all healthy and diseased people urine samples independently of detection of compound in a precise sample during GC/O analysis. Peak area of 2-methoxythiophene is referred to the only one control sample where it was detected.

Comparing data in Figures 1 and 2 it is clearly seen that the differences in odor activities of compounds are caused by roughly similar differencesin their contents in the samples based on GC/MS data. Statistically significant differences between the two groups were obtained for thiophene, dimethyl disulphide and phenyl-acetic acid (Figure 2). Although the peak area for 2-methoxythiophene appear to be the same between control samples and cancer’ patients in Figure 2, it is noteworthy that GC/MS detected this compound in only one of healthy controls while it was detected in about half of cancer patients.

Discussion

Fiction and action movies often show escaped prisoners chased by junkyard dogs, reminding us of the dog’s ability to recognize chemical mixtures and track them to their sources [30]. Crime-related chemical residues, such us narcotics and explosives, can be easily detected by well-trained sniffer dogs [31], [32]. The dogs’ sense of smell is highly developed; their olfaction allows them to perceive odorous compounds present in as little as parts per trillion [33], due to anatomical, physiological and genetic factors. Dogs perceive odours by sniffing, during which short air inhalations enter the nose and reach the olfactory receptors on neurons of the nasal olfactory epithelium. The axons of all these cells form the olfactory nerve bundles, which converge to the olfactory bulb in the brain. The perception of scent occurs in the frontal cortex [34]. In recent years, a dog’s ability to recognize, by sniffing, biological samples from cancer patients has emerged, so that the involvement of dogs in the clinical setting has been suggested since urinary volatile organic compounds (VOCs) have been proposed as useful biomarkers for assessing tumor presence [12], [13], [14]. Diagnosing cancer at its earliest stages is crucial to give patients the best chance of survival and treatment options [35]. Nowadays, scientists are struggling to discover novel biomarkers that may help in early and non-invasive diagnosis of malignancies. To date several clinical markers (mostly detected in the blood serum) have been proposed for GI cancers: the most frequently used both for pancreatic and for gastric cancer are the carbohydrate antigen 19-9 (CA 19-9) and the carcinoembryonic antigen (CEA) [1], [5], [36]. However, the sensitivity and specificity of these markers are inconsistent as they are unfrequently elevated in the early stage of the cancerogenesis [37], and may be over-expressed in various inflammatory conditions [38], [39]. Interestingly, the use of these and other proposed markers (such as a CEACAM1, CA-125 for pancreatic cancer) [40] has been assessed as a prognostic and surveillance rather than a diagnostic tool [1], [41].

Great effort has been devoted to studying VOCs [10], which may be differentially recognized by dogs in biological samples from healthy and diseased people [12], [13], [14]. Nevertheless canine olfactory detection in the clinical setting to help diagnosis has some limitations: i) dogs need to be well trained to recognize a particular odor signature, and this may be expensive and time-consuming [15]; ii) genetic factors such as a dog’s breed or polymorphisms in the olfactory receptors may influence the sensory ability of the animal [13], [16], so that performances from different dogs may be variable. Moreover, another disadvantage of using dogs to detect cancer is that it is still not known whether they recognize a single compound or a mixture of compounds [14], [42], while identifying individually the molecules that distinguish diseased from healthy samples could open the way to the discovery of new therapeutic targets.

For all these reasons, it would be desirable to set up alternative approaches to sniffer dogs, based also on automated systems which allow separation and identification of single compounds.

In order to shed light on what dogs actually detect in cancer samples and whether these compound(s) can be used as biomarker(s), we used GC/O as a diverse approach aimed at identifying a single or a panel of odor active compounds which could be measured in urine to discriminate between GI cancer carriers and cancer-free subjects, as it was already performed for other kinds of tumors using different techniques [13], [21], [23], [24], [25], [26], [27]. A well-established technique for VOC analysis in biological samples is represented by GC/MS. It should be considered, however, that not all VOCs are odor-active [43] and that is why traditional techniques based only on chemical detection of metabolites would not help understand the molecular bases of dogs’ cancer detection. Moreover, GC/O has the potential to detect compounds present at trace levels [19], which escape GC/MS detection but are sensed by GC/O due to their odorous properties. In our study, for example, this was the case of 4-(or 5-)methyl-3-hexanone, which was barely detectable by GC/MS but had a considerable odor activity. Moreover, the literature reports examples of urine compounds undetected with traditional techniques which were identified for the first time by GC/O [44]. Certainly human olfaction is much less sensitive than the canine olfaction. From the anatomic point of view, the olfactory epithelium of dogs is about 20-fold larger than in humans and can thus accommodate a greater number of neuronal cells and olfactory receptors [45]. Moreover, it is estimated that dogs possess an approximately 30% higher repertoire of genes encoding olfactory receptors when compared to humans, which in turn have a larger number of inactive pseudogenes [45]. Furthermore, it is believed that the way dogs sense the odours by sniffing makes perception more efficient than with normal breathing: briefly inspiring through the nostrils while the mouth is closed would reduce the distance between inhaled air and receptors in the nose, thus improving the olfactory acuity [31].

Although less sensitive than canine olfaction, however, it is documented that human olfaction is superior to any other chemical detector of odorous compounds [19], such as an electronic nose. For this reason, we considered GC/O combined with GC/MS a valid approach to pursue our aim in order to overcome the dog’s weaknesses mentioned above.

The data obtained in the current study indicated that dimethyldisulphide, 2-methoxythiophene and phenylacetic acid odor activities were elevated in cancer carrier’s urine and thiophene, 3-methyl-2-pentanone, 4-(or 5-) methyl-3-hexanone, 4-ethyl guaiacol odor intensities were higher in the urine of healthy people.

An increase in the content of 2-methoxythiophene has previously been observed in breast cancer cells [46] and an increase of dimethyl disulphide in melanoma cells [47] which parallel our results. However, in other kinds of cancers such as breast cancer [48], colorectal cancer, leukemia and Hodgkin lymphoma [28], dimethyl disulphide was found down-regulated compared to controls. Furthermore, while in our analysis 5-methyl-3-hexanone was found decreased in cancer patients compared to healthy controls, in a previous study on fecal samples it was found to be a marker of gastrointestinal disease [49], [50]. The reasons for some inconsistencies with previous studies might be due to individual differences in the patients, different biology of the tumors and/or differences in the method of VOC extraction and detection. As concerns the other four compounds we found altered, differences in the content of thiophene, 3-methyl-2-pentanone, phenylacetic acid and 4-ethyl guaiacol in metabolites of cancer patients have not been reported previously.

Possible causes for failure of finding, among odor-active compounds, a unique biomarker only present in cancer patients and not in controls, may be due to several factors: i) low concentration of analytes detected with very low MF(%); ii) genetic specificity of assessors; iii) lacking of a specific receptor for the compound in humans or compound concentration smaller than the odor treshold barrier for humans. Nevertheless, in the vast majority of literature reports and in our study, no unique biomarker was identified incancer patients’ samples compared to controls, but rather profiles of differentially represented compounds were found between the two groups [23], [25], [26], [27], [48].

Although further work is needed and larger cohorts of patients and controls should be analyzed, our preliminary results are encouraging and suggest that GC/O is a feasible and reliable method for the differential detection of VOCs in the urine of healthy and diseased people. Should the identified cancer-associated compounds be confirmed in a larger study, this would offer the potential for future development of screening tests which could be used in the clinical practice to support diagnosis.

Acknowledgments

The authors thank for the kind contribution of the spouses Mrs. Di Paola and Mr. Grimaldi ad memoriam of her beloved mother for the scientific research through Fondazione Italiana Biologi (FIB) (Grant/Award Number: “GAS16”).

References

  • 1.

    Anderson BW, Ahlquist DA. Molecular detection of gastrointestinal neoplasia: Innovations in early detection and screening. Gastroenterol Clin North Am 2016;45:529–42. CrossrefPubMedWeb of ScienceGoogle Scholar

  • 2.

    Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359–86. CrossrefPubMedWeb of ScienceGoogle Scholar

  • 3.

    Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87–108. CrossrefPubMedWeb of ScienceGoogle Scholar

  • 4.

    Fitzmaurice C, Dicker D, Pain A, Hamavid H, Moradi-Lakeh M, MacIntyre MF, et al. The global burden of cancer 2013. JAMA Oncol 2015;1:505–27. Web of ScienceCrossrefPubMedGoogle Scholar

  • 5.

    Jin Z, Jiang W, Wang L. Biomarkers for gastric cancer: Progression in early diagnosis and prognosis (Review). Oncol Lett 2015;9:1502–8. PubMedGoogle Scholar

  • 6.

    D’Aronzo M, Vinciguerra M, Mazza T, Panebianco C, Saracino C, Pereira SP, et al. Fasting cycles potentiate the efficacy of gemcitabine treatment in in vitro and in vivo pancreatic cancer models. Oncotarget 2015;6:18545–57. PubMedCrossrefGoogle Scholar

  • 7.

    Vaccaro V, Sperduti I, Vari S, Bria E, Melisi D, Garufi C, et al. Metastatic pancreatic cancer: Is there a light at the end of the tunnel? World J Gastroenterol 2015;21:4788–801. CrossrefWeb of ScienceGoogle Scholar

  • 8.

    Tavano F, Fontana A, Pellegrini F, Burbaci FP, Rappa F, Cappello F, et al. Modeling interactions between Human Equilibrative Nucleoside Transporter-1 and other factors involved in the response to gemcitabine treatment to predict clinical outcomes in pancreatic ductal adenocarcinoma patients. J Transl Med 2014;12:248. Web of ScienceCrossrefPubMedGoogle Scholar

  • 9.

    Moser E, McCulloch M. Canine scent detection of human cancers: A review of methods and accuracy. J Vet Behav 2010;5:145–52. Web of ScienceCrossrefGoogle Scholar

  • 10.

    Probert CS, Ahmed I, Khalid T, Johnson E, Smith S, Ratcliffe N. Volatile organic compounds as diagnostic biomarkers in gastrointestinal and liver diseases. J Gastrointestin Liver Dis 2009;18:337–43. PubMedGoogle Scholar

  • 11.

    Sarosiek I, Schicho R, Blandon P, Bashashati M. Urinary metabolites as noninvasive biomarkers of gastrointestinal diseases: A clinical review. World J Gastrointest Oncol 2016;8:459–65. PubMedWeb of ScienceCrossrefGoogle Scholar

  • 12.

    Lippi G, Cervellin G. Canine olfactory detection of cancer versus laboratory testing: myth or opportunity? Clin Chem Lab Med 2012;50:435–9. Web of SciencePubMedGoogle Scholar

  • 13.

    Cornu JN, Cancel-Tassin G, Ondet V, Girardet C, Cussenot O. Olfactory detection of prostate cancer by dogs sniffing urine: a step forward in early diagnosis. Eur Urol 2011;59:197–201. Web of SciencePubMedCrossrefGoogle Scholar

  • 14.

    Taverna G, Tidu L, Grizzi F, Torri V, Mandressi A, Sardella P, et al. Olfactory system of highly trained dogs detects prostate cancer in urine samples. J Urol 2015;193:1382–7. Web of ScienceCrossrefPubMedGoogle Scholar

  • 15.

    de Boer NK, de Meij TG, Oort FA, Ben Larbi I, Mulder CJ, van Bodegraven AA, et al. The scent of colorectal cancer: detection by volatile organic compound analysis. Clin Gastroenterol Hepatol 2014;12:1085–9. CrossrefWeb of SciencePubMedGoogle Scholar

  • 16.

    Lesniak A, Walczak M, Jezierski T, Sacharczuk M, Gawkowski M, Jaszczak K. Canine olfactory receptor gene polymorphism and its relation to odor detection performance by sniffer dogs. J Hered 2008;99:518–27. Web of SciencePubMedCrossrefGoogle Scholar

  • 17.

    Arasaradnam RP, Covington JA, Harmston C, Nwokolo CU. Review article: next generation diagnostic modalities in gastroenterology–gas phase volatile compound biomarker detection. Aliment Pharmacol Ther 2014;39:780–9. Web of SciencePubMedCrossrefGoogle Scholar

  • 18.

    Brattoli M, Cisternino E, Dambruoso PR, de Gennaro G, Giungato P, Mazzone A, et al. Gas chromatography analysis with olfactometric detection (GC-O) as a useful methodology for chemical characterization of odorous compounds. Sensors (Basel) 2013;13:16759–800. Web of SciencePubMedCrossrefGoogle Scholar

  • 19.

    Delahunty CM, Eyres G, Dufour JP. Gas chromatography-olfactometry. J Sep Sci 2006;29:2107–25. CrossrefPubMedGoogle Scholar

  • 20.

    Kusano M, Mendez E, Furton KG. Comparison of the volatile organic compounds from different biological specimens for profiling potential. J Forensic Sci 2013;58:29–39. PubMedCrossrefWeb of ScienceGoogle Scholar

  • 21.

    Mazzone PJ, Wang XF, Lim S, Choi H, Jett J, Vachani A, et al. Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer. BMC Cancer 2015;15:1001. PubMedWeb of ScienceCrossrefGoogle Scholar

  • 22.

    Huang J, Kumar S, Abbassi-Ghadi N, Spaněl P, Smith D, Hanna GB. Selected ion flow tube mass spectrometry analysis of volatile metabolites in urine headspace for the profiling of gastro-esophageal cancer. Anal Chem 2013;85:3409–16. PubMedCrossrefWeb of ScienceGoogle Scholar

  • 23.

    Hanai Y, Shimono K, Matsumura K, Vachani A, Albelda S, Yamazaki K, et al. Urinary volatile compounds as biomarkers for lung cancer. Biosci Biotechnol Biochem 2012;76:679–84. Web of ScienceCrossrefPubMedGoogle Scholar

  • 24.

    Khalid T, Aggio R, White P, De Lacy Costello B, Persad R, Al-Kateb H, et al. Urinary volatile organic compounds for the detection of prostate cancer. PLoS One 2015;10:e0143283. PubMedCrossrefWeb of ScienceGoogle Scholar

  • 25.

    Navaneethan U, Parsi MA, Lourdusamy D, Grove D, Sanaka MR, Hammel JP, et al. Volatile organic compounds in urine for noninvasive diagnosis of malignant biliary strictures: A Pilot Study. Dig Dis Sci 2015;60:2150–7. PubMedWeb of ScienceCrossrefGoogle Scholar

  • 26.

    Wang D, Wang C, Pi X, Guo L, Wang Y, Li M, et al. Urinary volatile organic compounds as potential biomarkers for renal cell carcinoma. Biomed Rep 2016;5:68–72. CrossrefWeb of SciencePubMedGoogle Scholar

  • 27.

    Arasaradnam RP, McFarlane MJ, Ryan-Fisher C, Westenbrink E, Hodges P, Thomas MG, et al. Detection of colorectal cancer (CRC) by urinary volatile organic compound analysis. PLoS One 2014;9:e108750. CrossrefPubMedWeb of ScienceGoogle Scholar

  • 28.

    Silva CL, Passos M, Camara JS. Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry. Br J Cancer 2011;105:1894–4. PubMedCrossrefWeb of ScienceGoogle Scholar

  • 29.

    Vene K, Seisonen S, Koppel K, Leitner E, Paalme T. A Method for GC/Olfactometry panel training. Chemosens Percept 2013;6:179–89. Web of ScienceCrossrefGoogle Scholar

  • 30.

    Pickel D, Manucy GP, Walker DB, Hall SB, Walker JC. Evidence for canine olfactory detection of melanoma. Applied Animal Behaviour Science 2004;89:107–16. CrossrefGoogle Scholar

  • 31.

    Gazit I, Terkel J. Explosives detection by sniffer dogs following strenuous physical activity. Appl Anim Behav Sci 2003;81:149–61. CrossrefGoogle Scholar

  • 32.

    Williams M, Johnston JM. Training and maintaining the performance of dogs (Canis familiaris) on an increasing number of odor discriminations in a controlled setting. Appl Anim Behav Sci 2002;78:55–65. CrossrefGoogle Scholar

  • 33.

    Quignon P, Rimbault M, Robin S, Galibert F. Genetics of canine olfaction and receptor diversity. Mamm Genome 2012;23:132–43. CrossrefPubMedWeb of ScienceGoogle Scholar

  • 34.

    Craven BA, Paterson EG, Settles GS. The fluid dynamics of canine olfaction: unique nasal airflow patterns as an explanation of macrosmia. J Royal Soc Interface 2010;7:933–43. Web of ScienceCrossrefGoogle Scholar

  • 35.

    Di Gangi IM, Mazza T, Fontana A, Copetti M, Fusilli C, Ippolito A, et al. Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites. Oncotarget 2016;7:5815–29. PubMedCrossrefGoogle Scholar

  • 36.

    Pavai S, Yap SF. The clinical significance of elevated levels of serum CA 19-9. Med J Malaysia 2003;58:667–72. PubMedGoogle Scholar

  • 37.

    Fontana A, Copetti M, Di Gangi IM, Mazza T, Tavano F, Gioffreda D, et al. Development of a metabolites risk score for one-year mortality risk prediction in pancreatic adenocarcinoma patients. Oncotarget 2016;7:8968–78. CrossrefPubMedGoogle Scholar

  • 38.

    Ranganathan P, Harsha HC, Pandey A. Molecular alterations in exocrine neoplasms of the pancreas. Arch Pathol Lab Med 2009;133:405–12. PubMedGoogle Scholar

  • 39.

    Urayama S, Zou W, Brooks K, Tolstikov V. Comprehensive mass spectrometry based metabolic profiling of blood plasma reveals potent discriminatory classifiers of pancreatic cancer. Rapid Commun Mass Spectrom 2010;24:613–20. PubMedCrossrefWeb of ScienceGoogle Scholar

  • 40.

    Wang S, Chen X, Tang M. Quantitative assessment of the diagnostic role of MUC1 in pancreatic ductal adenocarcinoma. Tumour Biol 2014;35:9101–9. CrossrefPubMedGoogle Scholar

  • 41.

    Brand RE, Nolen BM, Zeh HJ, Allen PJ, Eloubeidi MA, Goldberg M, et al. Serum biomarker panels for the detection of pancreatic cancer. Clin Cancer Res 2011;17:805–16. PubMedWeb of ScienceCrossrefGoogle Scholar

  • 42.

    Jezierski T, Walczak M, Ligor T, Rudnicka J, Buszewski B. Study of the art: canine olfaction used for cancer detection on the basis of breath odour. Perspectives and limitations. J Breath Res 2015;9:027001. PubMedWeb of ScienceCrossrefGoogle Scholar

  • 43.

    Friedrich JE, Acree TE. Gas Chromatography Olfactometry (GC/O) of Dairy Products. Int Dairy J 1998;8:235–41. CrossrefGoogle Scholar

  • 44.

    Wagenstaller M, Buettner A. Quantitative determination of common urinary odorants and their glucuronide conjugates in human urine. Metabolites 2013;3:637–57. CrossrefPubMedGoogle Scholar

  • 45.

    Quignon P, Kirkness E, Cadieu E, Touleimat N, Guyon R, Renier C, et al. Comparison of the canine and human olfactory receptor gene repertoires. Genome Biol 2003;4:R80. CrossrefPubMedGoogle Scholar

  • 46.

    Barh D, Carpi A, Verma M, Gunduz M. Cancer biomarkers: Minimal and noninvasive early diagnosis and prognosis. Boca Raton, Florida, USA: Taylor and Francis, CRC Press, 2014. Google Scholar

  • 47.

    Kwak J, Gallagher M, Ozdener MH, Wysocki CJ, Goldsmith BR, Isamah A, et al. Volatile biomarkers from human melanoma cells. J Chromatogr B Analyt Technol Biomed Life Sci 2013;931:90–6. PubMedCrossrefGoogle Scholar

  • 48.

    Silva CL, Passos M, Camara JS. Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers–a powerful strategy for breast cancer diagnosis. Talanta 2012;89:360–8. CrossrefWeb of SciencePubMedGoogle Scholar

  • 49.

    Garner CE, Smith S, de Lacy Costello B, White P, Spencer R, Probert CS, et al. Volatile organic compounds from feces and their potential for diagnosis of gastrointestinal disease. Faseb J 2007;21:1675–88. Web of ScienceCrossrefPubMedGoogle Scholar

  • 50.

    Kakuta S, Nishiumi S, Yoshida M, Fukusaki E, Bamba T. Profiling of volatile compounds in APC(Min/+) mice blood by dynamic headspace extraction and gas chromatography/mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2015;1003:35–40. CrossrefGoogle Scholar

About the article

Corresponding author: Dr. Valerio Pazienza, Gastroenterology Unit, I.R.C.C.S. “Casa Sollievo della Sofferenza” Hospital, viale dei Cappuccini n.1, 71013 San Giovanni Rotondo (FG), Italy, Phone: +39-(0)882.416281, Fax: +39-(0)882.416271

aConcetta Panebianco and Edgar Kelman contributed equally to this work.


Received: 2016-12-19

Accepted: 2017-04-16

Published Online: 2017-06-07

Published in Print: 2017-11-27


Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: The study was supported by a grant from the Italian Ministry of Health through Division of Gastroenterology (RC1403GA41 and RC1503GA40 to VP) IRCCS “Casa Sollievo della Sofferenza” Hospital and by the “5×1000” voluntary contributions. This research was supported also by European Regional Development Fund to Competence Center of Food and Fermentation Technologies (EU48667) and Institutional Research Funding to Tallinn University of Technology (IUT 19-27) of the Estonian Ministry of Education and Research and Industrie Alimentari Tamma s.r.l. (RV16GASTAMMA).

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


Citation Information: Clinical Chemistry and Laboratory Medicine (CCLM), Volume 56, Issue 1, Pages 138–146, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2016-1158.

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