Two-step investigation of lung cancer detection by sniffing dogs
Silvia Michela Mazzola1, Federica Pirrone1, Giulia Sedda2, Roberto Gasparri2, Rosalia Romano2, Lorenzo Spaggiari2,3 and Albertini Mariangela1
1 Department of Veterinary Medicine, Università degli Studi di Milano, Milan, Italy
2 Department of Thoracic Surgery, IEO, European Institute of Oncology IRCCS, Milan, Italy
3 Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
E-mail: [email protected] Received xxxxxx
Accepted for publication xxxxxx Published xxxxxx
Abstract
Early detection of lung cancer (LC) is a priority since LC is characterized by symptoms mimicking other respiratory conditions, but remains the leading cause of oncological disease death. Properly trained dogs can perceive the volatile organic compounds (VOCs) related to cancer, thanks to their acute sense of smell. Dogs' use for LC detection could be advantageous: reliable trained dogs would represent a valuable, cost-effective, non-invasive method of screening, which gives a clear-cut yes/no response. However, whether sniffer dogs are able to maintain their discriminative capacity at long-term control, and in different types of environments, needs further investigation. In this study, we sought to test two hypotheses: firstly, if dogs can be trained to perceive LC-related VOCs in human urine, a substrate which is not influenced by the carrier materials and may thus be a good candidate for large-numbers screening, and secondly, whether trained dogs retain their performance stable over time, even if the environment in which the tests are carried out varies. We have selected three family dogs that underwent a one-year training period (two weekly training sessions), by clicker training method. At the end of the training, dogs underwent two separate test phases, in two different locations, one year apart. All other procedures had been maintained unchanged. The donors of the samples submitted to the dogs were recruited by the European Institute of Oncology (IEO), Milan, Italy. Results show that dogs had different sensitivity (range: 45%-73%) and specificity rate (range: 89%-91%), and were deceived neither by lung conditions (that the dogs did not consider) nor by the existence of tumors in the beginning stage, that was correctly reported by dogs. The one-year interruption of the research work and the changes in the test environment did not induce statistically significant differences in the dogs' perceptive capacity. To our knowledge, so far, these issues have never been highlighted.
Keywords: lung cancer, sniffing dog, VOCs
1. Introduction 1
Cancer is one of the major public health problems worldwide: in 2015, 1.3 million people died from cancer in the EU, more 2
than one quarter (25.4 %) of the total number of deaths [1], and lung cancer accounted for more than one-fifth of all cancer- 3
related deaths. In 2015, the EU-28 standardized death rate for lung cancer was 54.0 per 100.000 inhabitants, with significant 4
differences between men and women (83.5 versus 31.5 per 100.000 inhabitants). The data for the United States are not very 5
dissimilar: according to the American National Center for Health Statistics (NCHS) mortality data, cancer is the second leading 6
cause of death, and lung cancer (LC) is the leading cause of death among both men and women affected by oncological disease 7
[2]. LC incidence data, collected in the USA by the National Cancer Institute’s, highlight a pattern that reflects trends in 8
behaviors associated with cancer risk, defined by smoking history and age: incidence rates have slightly decreased, faster in 9
men than in women, reflecting historical differences in tobacco use [3]. However, the 5-year survival rate for lung cancers is 10
only 18%, primarily because more than half of the cases are diagnosed at an advanced stage of the pathology. Early diagnosis 11
is a crucial factor for increasing the survival rates: nowadays only 15% of LCs are identified precociously [4] since the tumor 12
is characterized by asymptomatic onset or by respiratory symptoms mimicking other respiratory conditions. LC symptoms 13
usually appear at advanced stages of the disease, for instance when the mass compress other structures or nerves. For this 14
reason, new techniques to detect LC earlier in high-risk population of asymptomatic individuals could improve significantly 15
survival, reaching a 5-year survival rate between 70 and 90% [5,6].
16
Nowadays, screening of high-risk population is performed with low-dose computed tomography (LDCT), which showed a 17
reduction of 20% in LC mortalities compared to classical chest radiography [4]. However, the high costs, false-positive results, 18
and the exposure to potentially harmful radiation act as a limiting factor for the use of this technique in a clinical context. The 19
imaging criteria, in fact, could be insufficient for distinguishing early-stage lung cancer from benign nodules with decisive 20
confidence. Radiologists and chest physicians have highlighted that computerized tomography scanning technology does not 21
always have the power to discriminate between a large number of small lung nodules, which are, for the vast majority of them, 22
benign [7]. Therefore, the development of simple, easily accessible, and non-invasive screening techniques for detecting LC at 23
an early, curable stage is a pivotal priority [8,9].
24
In the animal kingdom, odors emitted from a body convey information about the metabolic and psychological status of an 25
individual. The human body emits a wide array of volatile organic compounds (VOCs), both odorous and non-odorous, which 26
can be different considering subject’s characteristics (e.g. age, diet, sex, physiological status, and genetic background). VOCs 27
are odorant molecules with molecular mass less than 400Da of various chemical classes, including alcohols, aldehydes, amides, 28
amines, carboxylic acids, esters, ethers, halides, heterocyclic compounds, hydrocarbons, ketones, nitriles, sulfides, terpenoids, 29
and thiols [10]. The VOCs mixture emitted by an individual is considered as ‘odor-fingerprints’ [11].
30
Pathological processes, including cancer cells growth and diffusion, can influence odor fingerprints: aberrant protein 31
synthesis and changed cells’ metabolisms produced different VOCs compared to healthy cells, or the ratio of VOCs that are 32
produced physiologically may change [4,5,8]. Thus, VOCs identification has been considered as a dynamic indicator of health 33
status. Numerous analytical techniques are used for VOCs analysis, including gas chromatography-mass spectrometry (GC–
34
MS) and Ion-mobility spectrometry (IMS), artificial electronic system (also known as electronic nose), sensor arrays proton 35
transfer reaction mass spectrometry (PTR-MS), selected ion flow tube mass spectrometry (SIFT-MS), tunable diode laser 36
absorption spectroscopy (TLDS) [11–13] The hypothesis that urine VOC profiles may be used to identify unhealthy individuals 37
has been tested on a variety of diseases, including celiac disease, inflammatory bowel disease, diabetes, urinary tract infections, 38
and tuberculosis [10,14]. To date, more than 100 volatile biomarkers have been studied, assessed and related to different type 39
of cancers [10,11,14,15]. In GC-MS studies on leukemia, colorectal cancer, and lymphoma, urinary VOCS identification have 40
produced promising results, encouraging further studies [8,10].
41
Several studies analyzed exhaled breath samples from patients with LC and identified a variable number of VOCs associated 42
to the disease with different combinations and quantities [11,13,15]. These data underline that applying the already mentioned 43
technique for cancer screening in oncology practice may be problematic due to this large variability, which also enhances the 44
complexity of the approaches and difficulties of results interpreting [10,14].
45
To date, detection dogs are considered as the most effective means of intercepting substances (explosives and other illegal 46
contraband) in highly demanding environments, even compared to advanced analytical chemical detection, thanks to their 47
unparalleled detection ability and relatively low cost [16] . The use of dogs for LC detection could be particularly advantageous:
48
thanks to their extremely acute sense of smell, dogs are virtually eligible to discriminate between innumerable scent qualities.
49
Several studies have highlighted that it is possible to train dogs to detect and discriminate, in different biological samples, 50
cancer-related VOCs odors [17], such as for bladder cancer [18], prostate cancer [19], skin melanoma [20], breast cancer [21], 51
ovarian cancer [22], and lung cancer [23,24]. These researches have shown that dogs are capable of identifying volatile marker 52
3
profiles associated with cancer, even if the accuracy data (sensitivities and specificities) are quite different among published 53
studies [17,21,23,25]. Differences in the methodological approach may underlie these variations [26–28], since the experience 54
and the disposition of working dogs’ [29], conditioning strategies [30,31] and trainers’ abilities and posture [32] may affect the 55
results. The importance of blinded settings is undeniable: with knowing the right answer, the trainer and the researchers 56
involved may unconsciously give signs to the dog, which leads the dog to respond correctly [33].
57
Reliable trained dogs would represent a valuable, cost-effective, and non-invasive method of screening for cancer diseases.
58
Compared to chromatography or mass spectrometry, sniffer dogs have some advantages: a trained dog’s response to a detected 59
odor (sitting or lying down) is a clear-cut yes/no response, which makes interpretation of the results immediate and 60
straightforward [13]. Furthermore, dogs’ mobility virtually enables detection in different sites outside a laboratory. However, 61
a dog’s reliability, environment influence on olfactory accuracy and context-related variability are still a matter of debate.
62
The studies regarding canine cancer detection suggest that dogs can indicate a cancer odor when trained with samples from 63
different donors, but the research is at an early stage [32]. Moreover, published studies differ with respect to the experimental 64
setup, biological samples type (e.g. breath, urine, tumor tissue, serum, etc.) and collection, dogs’ characteristics and training 65
methods, as well as in results presentation [9]. The analysis of the literature highlights some possible shortcomings in the 66
methodology: lack of matched controls; not reporting the presence of an external observer; the presence of samples from donors 67
affected by pathologies with similar symptomatology; pseudoreplication of samples during testing, potentially making them 68
familiar to the dogs [32]. There are still many aspects to be clarified, including how dogs learn these discrimination tasks and 69
which are the most appropriate methods to train them, in order to produce a reliable screening capability [28]. Articles published 70
so far provided only limited data on the progress made by dogs during training, and most of all, it has never been verified if the 71
cancer sniffer dogs maintain their discriminative capacity at long-term control varying some features of the test context.
72
Clarifying all these factors may be a crucial step to achieve the highest degree of accuracy, essential before sniffing dog cancer 73
screening can be adopted in clinical practice.
74
Our study aimed to test whether dogs, trained to indicate an odor associated with LC in human urine, retain their 75
performance stable over time, even if the environment in which the tests are carried out varies. For this purpose, we have 76
developed an experimental protocol with different steps. After a training period, which required a year of sessions twice a 77
week, dogs underwent two separate test phases, in two different locations, one year apart. The trainer, all the equipment and 78
the procedures had been maintained unchanged. None of the dogs showed statistically significant changes in discriminatory 79
sensitivity, and to our knowledge, this point had never been highlighted in the literature until now.
80
2. Methods 81
The data discussed here were collected from May 2017 to June 2018 at two facilities (Lodi and Milan) of the Department 82
of Veterinary Medicine, University of Milan, Italy.
83
2.1 Animals 84
After a screening phase, three out of six dogs originally involved in the study were selected to undergoing the entire training 85
session, while the others were exempted, due to low motivation for working in the scent lineup. Two females of Belgian 86
Malinois (Dixie and Bloom, 5 and 3 years, respectively) and a 3-year-old female mixed–breed (Helix) dogs underwent a one- 87
year training period (two weekly training sessions) by clicker training method (operant conditioning) with positive 88
reinforcement (food) to scent and recognize urine of people with LC.
89
The dogs were not used for other tasks during the study. All dogs were handled by professional dog trainers or behavioral 90
scientists during the training and testing sessions and were cared for by their owners between sessions.
91 92
2.2 Participant’s characteristics 93
The Division of Thoracic Surgery of the European Institute of Oncology (IEO), Milan, Italy, recruited patients and healthy 94
volunteers. The Institutional Review Board approved the study (R90/14-IEO102) and individual consent was obtained.
95
Oncological patients were subjects of both sexes, aged between 50 and 80, all diagnosed with LC by conventional bioptic 96
methods and scheduled for lung resection. None of the patients had a history of cancer within the previous five years and none 97
had received medical treatment before surgery in order to avoid potential therapy-induced alteration of the profile of urinary 98
VOCs.
99
4
Healthy eligible participants were subjects of both genders, aged between 50 and 80, without a referred history of oncological 100
findings confirmed by a recent (within the last 6 months) negative chest x-ray or Computed Thomography scan, and selected 101
as the control group.
102
Drugs, ethnicity, diet, alcohol consumption, smoking habits, and exposure to chemicals were not considered as exclusion 103
criteria. However, these factors were recorded to analyze their possible influence on the dog’s signaling. Subjects with 104
metastastic disease or with history of cancer in the previous 5 years or with neoadjvunant treatment were excluded.
105
Subjects were divided into three groups, as shown in table 1.
106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121
Tab.1 – Groups and sample size of training and trial phases.
122 123 124
2.3 Sample collection and handling 125
126
The samples were collected in the morning, directly into the Institute, with a volume of at least 25 mL. The urines were 127
placed in a sterile container (Pic Steril Box, Pikdare Srl, Como, Italy), refrigerated within 45 min and then stored and transported 128
to the laboratory of the testing center on a portable electric freezer at −20°C.
129
In the laboratory, the samples were defrosted in a 37°C water bath, and aliquoted into 0,5 ml hermetically sealed polymeric 130
tubes (Securitainer tube 29x63 mm, lot n. M609710, Nolato, Netherlands and Securitainer Closure 29 mm, lot n. M609615, 131
Nolato, Netherlands) and subsequently frozen. Only the progressive number of the donor was marked on the white polymeric 132
tubes. For presentation to the dogs, samples were defrosted and immediately used, in a wet state. Each sample was used only 133
for one session, and than discarded.
134 135
2.4 Sniffing room and experimental staff 136
137
Dog training was conducted at the Lodi’s Centro Zootecnico Didattico Sperimentale of the Department of Veterinary 138
Medicine of the University of Milan, in a dedicated room, isolated from external stimuli. Six sample stations, specially designed 139
for this study and constructed of heavy stainless steel and aluminum, were positioned in a single straight line, spaced 0.75 m 140
apart, on the floor as in Fig. 1(a). Secutainer tubes with urine samples were put into a metallic casing, protected by a perforated 141
metal cover, for the dogs to sniff. The urine was not visible or accessible to the dogs other than by olfaction through the six, 20 142
mm-diameter “scent holes”. To prevent cross-contamination, the experimenter wore nitrile gloves when handling sample tubes 143
and inserted them into the array using stainless steel forceps.
144
During the training procedure, 3 persons were present in the sniffing room:
145
1. The experimenter, who placed urine samples in the lineup and gave a signal to start a dog’s searching;
146
2. The dog handler, who encouraged the dog to sniff all stations in the lineup and, in the case of a correct indication, gave 147
an acoustic signal with a clicker device that emits a double-click sound and rewarded the dog with verbal praise and a piece of 148
food. After the dogs began to work autonomously, the handler was invisible to the dog, hidden behind a wooden screen placed 149
in the sniffing room, and blind to the position of the pattern sample in the lineup. In this case, the experimenter indicated to the 150
handler when the dog correctly signaled the positive sample, so that the handler could reward the dog.
151
Group Description Training phase
Trial phase n°1
Trial phase n°2
LC Lung cancer patients 118 11 11
PP
Patients with non- oncological lung chronic conditions
(e.g. Chronic obstructive pulmonary disease, asthma, emphysema,
etc)
33 11 11
H Healthy control
subjects 51 44 44
5
3. An observer who took care of the video registration and observation of the behavior of the dog and the handler, seated 152
motionless and in complete silence in a corner of the room.
153 154
2.5 Training procedure 155
156
The training procedure was based on operant conditioning, with a food reward (a couple of dog treats, Frolic complete, Mars 157
Italia, Assago, Italy) for correct behavior. The training has scheduled two test days per week, each with two sessions of at least 158
six runs, depending on the dog’s motivation. In each run, samples were selected to compose six-slot panels so that 1 sample of 159
LC Group and at least 1 sample of PP Group were compared with samples of healthy subjects, always varying the donors’
160
identity. The positions of the samples were randomly changed throughout the successive runs, in order to minimize position- 161
related interference. Moreover, since each dog carried out two sessions per day, at the end of each session the six-slot panels 162
were changed, and the sample station perfectly cleaned with a vapor machine (Vaporetto PRO 90 Turbo, Polti, Italy). Dogs 163
were asked to indicate the correct responses by sitting directly in front of the station containing the cancer sample (Figure 1 164
a,b).
165
During the training period, the dogs showed a different learning behavior but completed the training phase in approximately 166
the same time. After the training period, all dogs were able to detect one cancer sample out of six samples, as confirmed by at 167
least two correct runs in a row of three consecutive sessions.
168 169
2.6 First trial 170
171
The first set of test trials took place at Lodi’s Centro Zootecnico Didattico Sperimentale of the Department of Veterinary 172
Medicine of the University of Milan. During the trial phases, only the trainer was inside the room and, when the dog 173
performed the research work, he remained hidden by the wooden screen. The experimenter and the observer were in an 174
adjacent room, avoiding any interaction with the trainer and observing the dogs’ work through a computer screen connected 175
to the camera (Panasonic HC-V180, Japan), which was positioned on a tripod and operated remotely. In both trial phases, 176
each dog ran a single run, then ended its work and left the room, so he was not rewarded with food, but only verbally, 177
regardless of the sample indicated. Before the dog entered the room, a urine sample of a lung cancer patient (LC 178
Group) was randomly placed in the six sample stations among five control samples (PP and H Groups) by an investigator not 179
involved in other phases of the study. Thus, the team worked in a double-blinded setting during both tirial periods, as the 180
position of cancer and non-cancer samples in the sniffing station were unknown to trainer, researcher, and observer. To 181
ensure randomness, the True Random Number Generator was used (http://www.random.org), both for the selection of the 182
samples (of donors unknown to dogs) and for the positioning of the samples on the samples stations. The composition of the 183
panels of samples was the same for all dogs, but not the position of the samples on the sample stations. In each of the 11 test 184
days, every dog performed one run. For each run, a new sealed set of samples of donors, unknown to dogs’, was used for 185
each dog. The behavior and indications of dogs were video recorded (Panasonic HC-V180, Japan).
186 187
2.7 Second trial 188
189
In order to assess if cancer sniffer dogs maintain their discriminative capacity over time, also varying some features of the 190
test context, the second part of the working phase was conducted with the same dogs approximately one year after the first set 191
of experiment. During this time, dogs have never worked in olfactory research and have lived with their family.
192
The second set of test trials took place at Milan’s facilities of the Department of Veterinary Medicine of the University of 193
Milan. Before the tests, four training sessions (one per week) allowed the dogs to become familiar with the environment 194
(which was different from that of training and the first trial session), and to regain confidence with the trainer and the sniffing 195
work. In the second trial, to minimize the risk of interference on results, and to make success rate better comparison with 196
previous trial data, the room shape, the sample stations, and their alignment within the room were the same as those of the 197
first trial, as well as the trainer and the researchers involved in the study. All the experimental procedures adopted in the first 198
trial were unmodified: only the trainer was inside the room, hidden by a wooden screen as the dog performed the research 199
work, and the experimenter and the observer were in an adjacent room, avoiding any interaction with the trainer. To ensure 200
the double-blinded setting, the urine samples were randomly placed in the six sample stations, before the dog and the trainer 201
entered the room, by an investigator not involved in other phases of the study. New sealed samples of donors unknown to 202
6
dogs were used for each dog, in each run. The composition of the panels of samples was the same for all dogs, but not the 203
samples’ position on the sample stations. In each of the 11 days, dogs performed a single run, then ended their work and left 204
the room, being verbally rewarded regardless of the sample indicated. The behavior and indications of dogs were recorded.
205
2.8 Statistical analysis 206
207
Statistical analysis was performed using IBM SPSS Statistics for Windows, version 25.0 (Armonk, NY: IBM Corp). The 208
Wilcoxon signed-rank test for paired samples was used to detect statistically significant differences in the sensitivity, specificity 209
and success rates of the three dogs between first trial and second trial time points.
210
Diagnostic accuracy was calculated as sensitivity and specificity of a dog’s indication of samples compared with the true 211
diagnosis confirmed by TAC. Thus, the sensitivity refers to the conditional probability of the dog indicating cancer when the 212
condition was present, and specificity refers to the conditional probability of the dog ignoring a sample from a healthy donor.
213
Both sensitivity and specificity were expressed as proportions. Point estimates were calculated with 95% confidence intervals.
214
The probability of a perfect test run (finding the right sample and ignoring the controls) by chance was 1/6 (17%). All statistical 215
tests were 2-sided with exact p<0.05 considered statistically significant.
216
Pearson's chi-squared test of independence in 2 x 2 contingency tables was used to explore associations between either 217
patient- or testing-related variables and a dog’s correct response. The Fisher's exact test was performed in the analysis of 218
contingency tables when the expected frequency of the observations was lower than 5. Backward stepwise logistic regression 219
analyses were performed to identify factors influencing a dog’s correct response for which there were significant differences 220
in the Pearson's chi-squared test. All variables were entered into the model initially, with the least significant variables removed 221
one at a time until only significant variables associated with values of P≤0.05 remained. The significance of each predictor was 222
assessed with likelihood-ratio tests. If appropriate, binary logistic regression was also used to analyze factors for which the chi- 223
squared test did not find a significant relationship with the dog giving a correct response. The odds ratio was calculated to 224
evaluate the strength of such relationship. The Hosmer-Lemeshow test was used to assess the goodness of fit of the logistic 225
regression models. A two-sided P<0.05 was considered statistically significant.
226 227
3. Results 228
229
Applying the inclusion and exclusion criteria, 334 participants were enrolled (Table 2): 140 patients with histologically 230
confirmed LC (LC group), 55 patients with lung disease other than LC (PP group) and 139 healthy individuals (H group).
231 232 233 234 235 236 237 238
Tab.2 – Composition of patient’s and healthy subjects enrolled.
239
LC Group: lung cancer patients; PP Group: Not oncological lung conditions; H Group: Healthy subjects.
240 241
The distribution of active smokers was similar between groups. Subjects of PP group included three patients affected by 242
benign tumor (i.e. hamartoma) which are characterized by cartilage, fat, fibromyxoid connective tissue, smooth muscle, bone 243
and the risk of transformation into malignance is considered low [34]. None of them was recognized as positive sample by the 244
dogs. Table 3 shows some of the characteristics of donors enrolled in LC group, and the correctness of the signal given by the 245
dog in the two trial phases runs.
246
Table 4 shows dogs’ ability in detecting lung cancer related VOCs in the two trials. In the first trial Bloom sat in front of the 247
cancer sample in six runs, Helix in eight and Dixie in five runs on a total of eleven. In the second trial, performed one year after 248
the first trial, Bloom and Helix worsened their performance, with four and seven right responses respectively, while Dixie 249
improved her performance, sitting in front of the cancer sample for six times. The sensitivity and specificity values of Bloom 250
and Helix decreased in the second trial, while Dixie showed an increase in both parameters, also if these changes are not 251
statistically different between the two trials (Wilcoxon signed-rank test: Z= -0.535; p=0.593 and Z= 0.0; p=1.0 respectively).
252
LC Group PP Group H Group
Subjects 140 55 139
Age years 64.8 ± 9.3 64.9 ± 9.2 64.9 ± 9.2
Sex M/F 87/53 33/22 93/46
7
Even so, the success rate is not statistically changed in confront of the first trial (Wilcoxon signed-rank test: Z= -0.535;
253
p=0.593).
254
None of the factors considered shown to be associated with a dog’s correct response. Thus, binary logistic regression models 255
were not run.
256 257
4. Discussion 258
The present study shows that family dogs, trained by a professional trainer for the detection of VOCs markers of LC in 259
human urine, had a sensitivity rate that varied from 45% to 73% across the different dogs and a specificity rate that ranged from 260
89% to 91%. Moreover, dogs were deceived neither by lung conditions nor by benign tumors, such as the hamartoma.The one- 261
year interruption of the research work, without any form of training refreshment, and the changes in the test environment, did 262
not induce statistically significant differences in the dog's perceptive capacity. This data agrees with Wilson's highlighting, 263
which has deepened the critical role of memory in odor discrimination [35]. Based mainly on experimental models on rodents, 264
Wilson suggested that when an animal learns to perceive a mixture of odor composed of many hundreds of chemicals, he treats 265
it synthetically as an odor object, and he may retain memory for a long time. This factor would surely constitute a point in favor 266
of dogs' use in the perception of cancer VOCs, especially in pathology in which early diagnosis is essential, such as lung cancer.
267
It should be noted that, despite having opted for a training session frequency of 2 times per week, a frequency that proved 268
to be more efficient than a daily training, and for a short duration of the training session (less than 45 minutes), which proved 269
to be more efficient compared to longer training sessions [29,30] none of our dogs reached a better value of perceptive capacity.
270
One of the limits deriving from the use of dogs in detecting tumors could be the constancy of their effectiveness: unlike 271
technological device, dogs have physical needs and personality [21,23] they require daily care and attention and can work for 272
short periods before they get bored, distracted, hungry, thirsty, and sleepy. Furthermore, each dog needs a long period of 273
individual training, which does not always lead to the desired results. Moreover, dogs are extremely sensitive individuals and, 274
depending on their personality, could be affected by the variations in the environment around them, also on a social level, 275
regardless of the training received.
276
Our choice to train family dogs for this study had two purposes: first of all, to guarantee a high quality of life for dogs, 277
without depriving them of the affective experience of social life; we also wanted to verify if the performance of the dogs 278
involved in the study were stable over time, or were somehow impacted by the changes that inevitably take place in the family 279
life of individuals.
280
To the best of our knowledge, this is the first study in which dogs were trained to discriminate VOCS detectable in urine, 281
without being initially trained with tumor tissue samples [18,23,25,35,36]. Urine is a non-invasively collected biospecimen 282
which until now has not been widely used as a source of potential molecular biomarkers of LC [27,37]. Very low concentrations 283
of VOCs are present in the headspace gas of urine samples with an high level of subjects heterogeneity: in the urine of healthy 284
volunteers have been identified over 700 VOCs [14,37]. The composition of VOCs pattern is influenced by cells metabolic 285
features, which can be altered during pathological conditions, including cancer.
286
The collection and storage procedures of urine samples, compared to those of exhaled air, are more straightforward and less 287
influenced by external factors, such as the possible interference with the ambient air in which the sample is collected [5].
288
Walczak’s study [28] evidenced that the ambient air present in hospital rooms may get into the exhaled air samples collected 289
from donors, acting as confounding factors for dogs that may become conditioned to a specific hospital odor. Other factors, 290
such as smoking and eating habits of the donors, may be relevant to considerate in the procedure of breath air collection samples.
291
On the contrary, urine sampling is a subjects-friendly method, does not require special precautions or prescription, and the dog's 292
perception of the VOCs profile would not seem to be influenced by the environment in which the sample was collected [27].
293
These characteristics led to our decision to opt for the use of urine samples in this study: the awareness that it was possible to 294
avoid several potential confounding agents, associated with the greater manageability of the samples, also linked to their 295
preservability and the possibility of transport without special precautions. These factors would be indeed helpful and 296
appreciated in a future perspective of large-scale screening of subjects.
297 298
5. Conclusion 299
300
Our results constitute a step forward in the study of the perception of LC by dogs: the data we have obtained show that dogs 301
can be trained to perceive VOCs directly from the urine of LC patients, without having to be sensitized by research on tumor- 302
based tissue [23]. The use of urine samples allows access from the early stages of the training phase to a higher number of 303
8
positive samples, increasing their variability significantly and, consequently, limiting the possibility that the dog will learn to 304
recognize the donor. A cancer detection dog is expected to match an odor sample in the lineup with the cancer odor pattern he 305
has fixed in its long-term olfactory memory during the training phase. Therefore, it is essential that in that phase, dogs could 306
be trained with a more significant number of positive samples.
307
Analyzing the test session passages of our dogs, it was possible to highlight that only for two positive samples (out of the 22 308
considered in total), all three dogs did not recognize the positivity of the sample. In one of these two cases, the urine sample 309
was donated by a patient suffering from an atypical carcinoid lung tumor. The particular nature of this tumor, derivative of the 310
salivary glands, could be related to the production of VOCs different from that of the other types of mostly diffuse LC histology 311
(e.g. adenocarcinoma) to which the dogs were trained [14,27]. All the other 20 positive samples used in the two olfactory test 312
sessions were recognized as such by at least one dog. None of the testing-related variables explored resulted statistically 313
associated with the dog’s correct response, according to what has been observed in previous studies, on other types of tumors.
314
Ultimately, our study showed that family dogs could be trained successfully for the perception of VOCs emitted by LC using 315
urine samples and that a prolonged interruption of the olfactory research work and the change of environment did not 316
significantly affect the perceptive abilities of dogs. However, it should be emphasized that dogs, sentient creatures, unlike 317
electronic equipment, need time, care, patience, and a sort of stability in the general living conditions.
318
The present study represents a side project of the human breath analysis study carried out by the European Institute of 319
Oncology colleagues, which demonstrated that the electronic nose might distinguish the exhaled breath of lung cancer patients 320
from those of healthy controls [4]. To date, different techniques for breath analysis have been described that vary for laboratory 321
instrumentation, sampling methods, and statistical analyses used. All these approaches have advantages as well as potential 322
drawbacks, and none have a real clinical adoption.
323
Our future work will involve a hybrid study approach, which will combine, on the same patients, sniffer dogs' urine detection 324
with exhaled breath electronic nose analysis: it is growing the awareness that the combination of different chemical 325
measurements may exert benefit [38]. Urine metabolomics could be intersected with other -omics profiles, to obtain a more 326
comprehensive view of the status of the patient, and a more specific panel of biomarkers [39]. These compounds detectable in 327
different body fluids (e.g., breath, urine, and sweat), and thus their profile may represent an overall expression of the different 328
metabolism characteristics of cancerous cells.
329
With the aim to accelerate the diagnosis of LC, and consequently to improve chance of healing, the work of sniffing dogs 330
could be a valid support to traditional electronic methods in order to improve the limits encountered by technology so far and 331
expedite the achieve of early diagnosis reliable methods.
332 333
Acknowledgements 334
This work was supported by Fondazione Cariplo, Grant No. 2014-0105. We want to thank Marco Sincovich for his valuable 335
contribution in dog training and we are very grateful to Aldo La Spina and the charity Medical Detection Dogs Italy for their 336 support.
337
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431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451
Table 3. Characteristic of LC Group donors (Trial phases runs) and signal given by dogs 452
453
12
DOG Id
donor
Right answer
Hystology Tumor
stage
Gender Smoker Ex smoker (years)
Drug Drug category
DIXIE 29 Yes Adenocarcinoma M No Yes - 8 No
BLOOM Yes
HELIX Yes
DIXIE 32 Yes Adenocarcinoma IB M No Yes - 1 No
DIXIE 38 Yes Adenocarcinoma F Yes No No
BLOOM Yes
HELIX Yes
BLOOM 39 No Adenocarcinoma IIIB M No No Yes Nebivolol
(beta-blockers);
Hydrochlorothiazide (diuretic);
Amlodipine (Calcium Channel Blockers)
HELIX Yes
DIXIE 43 No Adenocarcinoma IIIA M Yes No No
BLOOM Yes
HELIX Yes
DIXIE 47 Yes Adenocarcinoma IIB M No No Yes alfuzosin (alpha
blockers)
BLOOM No
HELIX No
HELIX 75 Yes Adenocarcinoma IIIA M Yes No Yes Acid acetilsalicilic;
repaglinide (antidiabetic);
Sitagliptin (antidiabetic), Metformine (antidiabetic), perindopril (ACE inhibitor), Amlodipine (Calcium Channel Blockers); Doxazosin (alpha-1 receptor antagonists);
Nebivolole (beta- blockers);
Indapamide (diuretic);
Atorvastatine (statine);
brinzolamide ( eye drops; carbonic anhydrase inhibitor); timolol (eye drops; non-
13
selective beta blocker).
DIXIE 76 No Adenocarcinoma IA M No Yes - 7 No
BLOOM Yes
DIXIE 77 Yes Squamous-cell
carcinoma
IIB F Yes No No
DIXIE 88 No Adenocarcinoma IA M No No No
BLOOM Yes
HELIX Yes
DIXIE 94 No Adenocarcinoma IA F Yes No Yes Lorazepam
(benzodiazepine)
BLOOM No
HELIX No
DIXIE 103 No Adenocarcinoma IB M Yes No Yes warfarin sodium
(anticoagulant);
acetylsalicylic acid;
delorazepam (benzodiazepine)
BLOOM Yes
HELIX Yes
BLOOM 109 No Atypical carcinoid IIA M Yes No No
HELIX No
BLOOM 133 No Adenocarcinoma IA F No Yes - 1 Yes
HELIX Yes
DIXIE 200 No Adenocarcinoma IB F No No Yes Beclometasone
(cortisoateroid);
Pantoprazole (proton pump inhibitor)
BLOOM No
HELIX Yes
DIXIE 226 Yes Squamous-cell
carcinoma
IIIA F Yes No Yes Carvedilol (beta-
blockers); Valsartan (Angiotensin II receptor blocker)
BLOOM No
HELIX No
DIXIE 232 No Squamous-cell
carcinoma
IA M Yes No Yes Acid acetilsalicilic
BLOOM Yes
HELIX No
DIXIE 241 Yes Adenocarcinoma IIIA F Yes No No
BLOOM Yes
HELIX No
DIXIE 246 Yes Squamous-cell
carcinoma
IB M Yes No Yes Amlodipine
(Calcium Channel Blockers);prednison e (corticosteroid);
simvastatin (statin)
BLOOM No
HELIX Yes
14
454
455 456 457 458 459
Table 4. Canine ability in detecting lung cancer related VOCs in the two trials.
460
Dog ID Parameter Estimate 95% CI Estimate 95% CI
Lower Upper Lower Upper
First trial Second trial
Sensitivity 0,55 0,49 0,61 0,36 0,29 0,43
DIXIE 249 Yes Squamous-cell
carcinoma
IA M Yes No Yes Losartan
(Angiotensin II receptor blocker);
BLOOM No
HELIX Yes
DIXIE 251 Yes Adenoid cystic carcinoma
IIA M No No No
BLOOM No
HELIX Yes
DIXIE 256 No Adenocarcinoma IB F No Yes -35 Yes Levothyroxine
BLOOM Yes
HELIX No
DIXIE 268 No Squamous-cell
carcinoma
IA M No Yes - 13 Yes bisoprololo (β1-
adrenergic blocking), acetylsalicylic acid;
Levothyroxine;
Pancrelipase;
Polyenoic fatty acids; Insulin;
BLOOM Yes
HELIX Yes
DIXIE 292 Yes Adenocarcinoma IIA F No Yes - 25 Yes bisoprolol (beta-
blockers)
BLOOM No
HELIX Yes
DIXIE 299 No Adenocarcinoma IB M Yes No No
BLOOM No
HELIX Yes
15
Bloom
Specificity 0,91 0,89 0,92 0,87 0,85 0,89
Success rate 54,54% 36,36%
Sensitivity 0,73 0,69 0,77 0,64 0,59 0,69
Helix
Specificity 0,91 0,94 0,96 0,93 0,92 0,94
Success rate 72,72% 63,64%
Sensitivity 0,45 0,38 0,52 0,55 0,49 0,61
Dixie
Specificity 0,89 0,87 0,91 0,91 0,89 0,93
Success rate 45,45% 54,55%
CI: confidence interval. Success rate: percentage of success among each trial's 11 runs.
461
462
463 464 465 466 467 468 469
16
Figure 1. Dogs indicate the correct position responses by sitting directly in front of the sample station, specially 470
designed for this study and constructed of heavy stainless steel and aluminum, positioned in a single straight line, 471
spaced 0.75 m apart, on the floor. In a: Bloom; in b: Helix.
472 473 474 475
