Isolation of Oral Bacteria, Measurement of the C-Reactive Protein, and Blood Clinical Parameters in Dogs with Oral Tumor

Setthawongsin, Chanokchon; Khunbutsri, Duangdaow; Pisamai, Sirinun; Raksajit, Wuttinun; Ngamkala, Suchanit; Jarudecha, Thitichai; Meekhanon, Nattakan; Rungsipipat, Anudep

doi:https://doi.org/10.1155/2023/2582774

Veterinary Medicine International

On this page

Abstract Introduction Materials and Methods Discussion Conclusion Data Availability Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 2582774 | https://doi.org/10.1155/2023/2582774

Isolation of Oral Bacteria, Measurement of the C-Reactive Protein, and Blood Clinical Parameters in Dogs with Oral Tumor

Chanokchon Setthawongsin,¹Duangdaow Khunbutsri,²Sirinun Pisamai,³Wuttinun Raksajit,¹Suchanit Ngamkala,¹Thitichai Jarudecha,¹Nattakan Meekhanon,¹and Anudep Rungsipipat⁴

Academic Editor: Imtiaz Rabbani

Received29 Jul 2022

Revised17 Feb 2023

Accepted04 Mar 2023

Published22 Mar 2023

Abstract

Canine oral cancers have a poor prognosis and are related to chronic inflammation. This may pose a risk of secondary bacterial infection. This study aimed to compare the bacteria isolated from oral swab samples, values of C-reactive proteins (CRPs), and clinical blood profiles of dogs with and without oral mass. A total of 36 dogs were divided in three groups: no oral mass (n = 21), oral mass (n = 8), and metastasis groups (n = 7). Significantly, both the clinical groups (the oral mass group and metastasis group) showed anemia, a decrease in the albumin-to-globulin ratio (AGR), and an increase in the neutrophil-to-lymphocyte ratio (NLR), globulin-to-albumin ratio (GAR), CRP, and CRP-to-albumin ratio (CAR) compared to the normal group. CAR showed an increasing trend in the oral mass and metastasis groups (10 times and 100 times, respectively) compared to the no oral mass group (). Neisseria spp. (20.78%) was the main isolated bacteria in all groups. The main genera in the no oral mass group were Neisseria spp. (28.26%), Pasteurella spp. (19.57%), and Staphylococcus spp. (19.57%). Neisseria spp., Staphylococcus spp., Klebsiella spp., and Escherichia spp. were found equally (12.5%) in the oral mass group. Escherichia spp. (26.67%), Pseudomonas spp. (13.33%), and Staphylococcus spp. (13.33%) were the main genera in the metastasis group. Interestingly, Neisseria spp. decreased in the clinical groups (Fisher’s exact = 6.39, ), and Escherichia spp. increased in the metastasis group (Fisher’s exact = 14.00, ). The difference of oral bacteria in clinical dogs compared to healthy dogs may be related to microbiome alterations, and both the clinical groups showed the increment of inflammatory biomarkers. This suggested that further studies should be conducted on the correlation between the specific bacteria, CRP, blood clinical parameters, and type of canine oral mass.

1. Introduction

Nowadays, cancer is the most common diseases in both dogs and human. The dogs and their owners share the same environment [1]. Many studies revealed that they response to the carcinogens from the environment in the same manner. For example, tobacco smoke was related to the increasing incidence of the upper respiratory tract cancer and oral cancer [2]. Head and neck cancers (HNC), especially oral cancers, are often classified as serious diseases in dogs. The most common type of oral cancer in dogs is oral melanoma which is followed by oral squamous cell carcinoma (SCC). Oral melanoma in human presents the high aggressive behavior. Canine oral melanoma shares the similar features and characteristics with human oral melanoma. It has been argued that the spontaneous oral cancer in dogs may be a good model and the comparative study for human cancer [1]. Benign tumors, such as fibromatous epulis, ossifying epulis, and acanthomatous ameloblastoma, show slow progress and are curable by excision surgery [3, 4]. On the other hand, oral melanoma and SCC show aggressive behavior, a high metastasis rate, poor prognoses, and short survival times [5, 6].

In human research, chronic inflammation of oral cancer has been observed. Most of them trigger inflammatory responses and induce chronic inflammation status. Tumor-promoting inflammation may play an important role in steps of cancer progression as mentioned by Hanahan and Weinberg [7]. An increase in clinical blood parameters related to inflammation may indicate the existence of cancer or tumors. The concentration of the C-reactive protein (CRP), an acute phase protein, is rapidly rising in response to trauma [8], inflammation [9–11], infection [12–16], and several malignancies [8, 17–19]. The elevated CRP levels are the essential information for diagnosis and prognosis not only in human medicine [20–22] but also in veterinary clinical medicine [16, 17, 23–27]. A previous report identified CRP and serum amyloid A (SAA) as diagnostic markers and prognostic indications after treatment of inflammation for the bacterial pneumonia [15]. CRP, SAA, and haptoglobin were detected and a significant increase in the canine mammary cancer such as anaplastic carcinoma, complex adenocarcinoma, simple adenocarcinoma, and SCC with metastasis, which characterized in the clinical stage IV–V or by a mass diameter greater than 5 centimeters with ulceration and secondary inflammation, was seen. Conversely, these dogs had the decreasing albumin concentration [17]. Moreover, canine mammary carcinoma showed a high concentration of CRP. This suggested that an inflammatory response is associated with this type of cancer [27]. In addition to mammary cancer, elevated concentration of CRP was detected in hemangiosarcoma, nasal adenosarcoma, cholangiocellular carcinoma, acute lymphoblastic leukemia, malignant histiocytosis, lymphoma, malignant mesothelioma [26], and neuroendocrine carcinoma [28]. The α₁-acid glycoprotein (AAG) and CRP were increased after operations to remove malignant cancer from the dogs and these acute-phase proteins again increased further after recurrences and metastasis [8].

Canine oral microflora comprised numerous resident bacteria [29–33]. These bacteria communities can play an essential role in interactions with host immunity [34]. The population and ecological system of the oral microbial agents can be changed as the host’s health changes [34–38]. Many studies reported that the microbiome could either directly or indirectly increase the chances of developing cancers in human and animal specific pathogen models. For example, the formation of mice colon cancer and hepatocellular carcinoma is promoted by Helicobacter hepaticus infection [39, 40]. In addition, chronic infection of enteropathogenic Escherichia coli can result in colon cancer [41]. The specific bacterial pathogen promotes tumor formation and progression that is the principal mechanism of microbiota related to human SCC, gastric cancer, colorectal cancer, and melanoma [34, 38, 41–44]. Recently, the impact of microbiome related to the process of cancer development was summarized as a new hallmark of cancer [45]. Canine oral cancers with progression and chronic inflammation can break or decrease the host’s oral mucosal defenses, and the failure of the host barrier may increase the risk of dysbiosis or the development of persistent or recurrent bacterial infection. This might be the result from persistent mucosal and/or epithelial cell colonization by microorganisms [46]. The advancement in bacterial identification with polymerase chain reaction (PCR) amplified 16S sequences. Dewhirst et al. found that the bacterial content in the dog mouth differs from that in the human mouth, and there were only 16.4% shared bacterial types in the dogs and human [47]. Ruparell et al. compared the microbiota from different areas within the canine oral cavity and found three niches (soft tissue surface, hard tissue surface, or dental plaque and saliva) in which the bacterial community profiles differed [33]. deCarvalho et al. compared the oral swabs from the normal dogs and the canine oral melanoma dogs. They found that Tannerella forsythia and Porphyromonas gingivalis from the subgingival plaque samples were significantly increased in canine oral melanoma dogs compared to the control dogs. These bacterial species are related to the periodontal diseases and human esophageal cancer [48]. So far, there are few studies that compare the oral bacteria of healthy dogs and dogs with oral cancer. The information of oral bacteria in canine oral tumors is limited and unclear. More information and knowledge about the bacterial population and the microbial alteration in the dog’s mouth and the clinical blood profiles might help us to increase the understanding about the role of oral bacteria and the blood profile in canine oral tumor and cancer.

For providing more information of canine oral cancer, this study investigated the oral swab bacteria using the culture dependent method with 16s rRNA gene sequencing identification and the clinical blood profiles of the dogs with and without oral mass. We focused on identifying culturable bacteria living in the oral mucosal surface of dogs. Thus, the purposes of our study were to compare the bacteria isolated from canine oral swab samples, values of C-reactive proteins (CRPs), and clinical blood profiles of dogs with and without oral mass.

2. Materials and Methods

2.1. Animals and Sample Collections

The thirty-six dogs in this observational prospective study were invited from the private animal hospitals in Bangkok and vicinity between June 2019 and March 2021. All the dog owners gave informed consent for sample collections from their dogs to be used for research purposes only (ACKU62-VTN-010). The signalment information included sex, age, and breed that were recorded. The dogs that had visited the small animal hospitals for the routine annual vaccination program and whose physical examination revealed no evidence of oral mass or serious clinical illness were included in this study as the “no oral mass” group or normal group (n = 21). In this group, there were 9 male and 12 female dogs. Their ages were between 6 and 13 years. The clinical group or the “oral tumor-bearing” group included dogs that presented with mass in their mouths during physical examination (n = 15) and/or had a later appointment for the surgical removal of an oral mass. Based on the definitive diagnosis from histopathological examination and clinical staging of fifteen dogs in the clinical group, eight dogs were classified in the oral mass group and seven dogs were classified in the metastasis group. In both clinical groups, there were 8 male and 7 female dogs. Their age was between 4 and 16 years (Table 1) (Figure 1).

All owners were asked to feed their dogs with commercial diets free of raw meat or milk products. The dog’s diets were managed to prevent oral contamination from raw food and fecal matter. An oral swab sample was collected from the tongue’s dorsum mucosa and the mucosa of the hard palate of each dog. The oral swab sampling was performed after 12 hours of fasting. The swabs were then transported in the Stuart transport medium (Yangzhou Chuangxin medical device factory, Yangzhou city, Jiangsu, China) from the animal hospital to the faculty of Veterinary Technology, Kasetsart University under cold transport, 4°C. Then, the bacterial culture was performed. Blood samples were collected and kept in the EDTA tube and Heparin tube for hematology and blood chemistry profile analysis, respectively.

In the oral mass group and the metastasis group, the oral swab, blood collection, and excision or incision biopsy were performed under anesthesia. The tissue from the oral mass was sent to the veterinary pathologists for diagnosis, and finally, a histopathological definitive diagnosis was received.

2.2. Clinical Laboratory Examination

The medical records include age, gender, clinical signs, histopathological diagnosis, complete blood count (CBC), the blood urea nitrogen (BUN) level, the creatinine (CRE) level, the alanine aminotransferase (ALT) level, the alkaline phosphatase (ALKP) level, total protein (TP), albumin concentration (ALB), globulin concentration (GLOB), and CRP concentration.

The CBC results were analyzed using an automatic analyzer (ProCyte Dx Hematology Analyzer, IDEXX Laboratories, Inc. USA). The BUN, CRE, ALT, ALKP, TP, ALB, and GLOB levels were measured using automatic blood chemistry measurement equipment (Catalyst One Chemistry Analyzer, IDEXX Laboratories, Inc., USA).

The plasma CRP concentration was measured using a commercial fluorescent immunoassay (Vcheck Canine CRP 2.0 Test Kit, Bionote, Gyeonggi-do, South Korea). In brief, five microliters of each plasma sample from all dogs were diluted with the diluent buffer (to 100 μl), mixed thoroughly, and aliquoted to the test device (V200 Analyzer, Bionote, South Korea). The plasma CRP concentrations were recorded for further statistical analysis. As part of routine diagnosis, CRP concentration results below the detection limit for the assay were set as less than 10 mg/L.

2.3. Bacterial Culture, Isolation, and Identification

An oral swab was cultured on blood agar (BA) and MacConkey agar at 37°C for 24–48 hours. All different predominant colonies that grew in the last plane of agar were selected. The predominant selected morphology colony obtained from each sample was further cultured on BA to obtain a pure culture. Genomic DNA from each pure isolate was extracted using E.Z.N.A.® Bacterial DNA kit (Omega Bio-Tek, Doraville, GA, USA) following the manufacturer’s instructions. The extracted bacterial DNA of isolates was identified using 16S rRNA gene sequencing by U2Bio Thailand (Bangkok, Thailand) and Bionics Co. Ltd. (Seoul, Korea). The extracted bacterial DNA was prepared for the identification step using 16S rRNA gene sequencing. The 16S rRNA gene was amplified with the pair of primers 518F (5′-CCAGCAGCCGCGGTAATACG-3′) and 800R (5′-TACCAGGGTATCTAATCC-3′). The thermocycler conditions were a predenaturation at 94°C for 4 min; 25 cycles of 94°C for 20 sec, 50°C for 40 sec, 72°C for 90 sec; a final extension step at 72°C for 3 min, and hold temperature at 4°C. PCR product was generated. Then, sequencing was performed after purification with ABI3730XL Sequencer (Thermo Fisher Scientific, Massachusetts, USA) by the Sanger sequencing method.

The nucleotide sequences were processed and assembled using BioEdit and the contig assembly program. The percent identity of bacterial isolates was determined using the BLAST server (https://blast.ncbi.nlm.nih.gov/Blast.cgi) of the National Center for Biotechnology Information (NCBI). The highest score and the closest relatives of the 16S rRNA gene were evaluated. Similarities to 16S rRNA gene sequences of the isolates that were ≥99% were used as criteria for identification.

2.4. Statistical Analysis

In this study, a variable was considered as a normal distribution when the value of the Shapiro‐Wilk test was larger than 0.05. The clinical blood profile data were showed as mean ± standard deviation (SD) when they were the normal distribution or showed as median with the interquartile range (IQR) when they were the non-normal distribution. Continuous variables in the normal distribution (ALB, AGR, and CRE) among three groups were compared using a one-way ANOVA test. Post hoc multiple comparisons were performed using the Bonferroni test. The non-normal distribution of continuous variables (RBC, WBC, PLT, NLR, TP, GLOB, GAR, CRP, CAR, BUN, ALT, and ALKP) among three groups was analyzed using the Kruskal–Wallis test. Differences in the two groups were analyzed by the Mann–Whitney U test. The oral bacterial isolates were presented on percentage. The Fisher’s exact was used to assess the relationships of variable-bacterial profiles to the groups of dogs. Multinomial logistic regression analysis was used to estimate the relative risk ratio (RRR) among the groups of variables. All data were facilitated by the STATA statistics analysis (StataCorp LLC, Texas, USA; serial number 401506228202), and was considered significant. The graphs of variables were created using the GraphPad prism program (GraphPad Software, San Diego, USA) and Microsoft Excel program (Microsoft 365, Washington, USA).

3. Result

3.1. Animals

Thirty-six dogs were included in this study. Twenty-one dogs (9 males and 12 females) were classified into the group of no oral mass dogs. They were 6–13 years old. In the two clinical case groups, there were 15 oral tumor-bearing dogs (8 male and 7 female). The age of dogs in this study was between 4 and 16 years old (Table 1). The increase of age did not increase the risk ratio in the oral mass group (RRR = 1.11, 95% CI: 0.84–1.48) and the metastasis group (RRR = 1.38, 95% CI: 0.98–1.95) when evaluated based on the no oral mass group () (Table 2). The proportion of female and male dogs that had oral masses or metastasis did not differ when evaluated based on the no oral mass group () (Table 2).

In the oral mass group, there were two cases of benign oral tumors in clinical stage I, which were acanthomatous ameloblastoma (n = 2), and six cases of malignant oral tumor with clinical stage II and III which were oral malignant melanotic melanoma (n = 1), oral SCC (n = 2), oral fibrosarcoma (n = 1), and oral malignant amelanotic melanoma (n = 2) (Table 3) (Figures 2(a) and 2(b)). In the metastasis group with clinical stage IV (regional lymph node metastasis and/or pulmonary metastasis), there were oral malignant melanotic melanoma (n = 3), oral chondrosarcoma (n = 1), oral squamous cell carcinoma (n = 1), and oral fibrosarcoma (n = 2) (Table 4) (Figures 2(c), 2(d), 3(a), and 3(b)). The dogs in the clinical case groups showed the clinical signs related to the oral mass such as hypersalivation, halitosis, dysphagia, and bleeding from mass. There was a dog (Case 1) in the metastasis group that presented lethargy and panting sign.

3.2. Clinical Laboratory Results

According to the CBC results, the median RBC in the oral mass group and metastasis group decreased when compared with the no oral mass group () (Figure 4(a) and Table 5). The dogs in both clinical groups exhibited anemia. The proportion of dogs that had low RBC levels in the oral mass group (RRR = 12.74, 95% CI: 1.03–157.02) and the oral mass with the metastasis group (RRR = 12.74, 95% CI: 1.03–156.98) were more than the no oral mass group (, borderline significance) (Table 6). There was a trend toward an increase in WBC in the clinical groups (). Moreover, the NLR in both the clinical groups showed a trend to increase when compared to the no oral mass group, and it was significantly increased in the metastasis group when compared to the no oral mass group () (Figure 4(b) and Table 5). The median of platelets in the metastasis group was significantly higher than in the no oral mass group () (Figure 4(c) and Table 5). Only the metastasis group showed an increasing level of platelets compared to the normal reference range. The clinical blood chemistry profiles of the three groups were in the normal reference range. However, the median plasma ALKP in the metastasis group was significantly higher than those in the no oral mass group () and the oral mass group () (Figure 4(d), Table 5).

(a)

(b)

(c)

(d)

Plasma TP, ALB, GLOB, CRP, AGR, GAR, and CAR are presented in Table 5 and Figure 5. The protein level in all groups was in the normal reference range. The TP was not different among the three groups of dogs (Table 5). ALB and GLOB showed the opposite trend. The ALB showed decreased levels in both the clinical groups; conversely, the GLOB showed increased levels in both the clinical groups (Figures 5(a) and 5(b)). The mean ALB and the median of the AGR in the two clinical groups were significantly lower than in the no oral mass group () (Figures 5(a) and 5(c)). Moreover, AGR in the metastasis group was significantly lower than the oral mass group () (Figure 5(c)). Conversely, the median of plasma GLOB levels in the oral mass group () and the metastasis group () were significantly higher than the no oral mass group (Figure 5(b)). GAR in the oral mass group () and the metastasis group () was significantly higher than the no oral mass group. In addition, GAR in the metastasis group was significantly higher than the oral mass group () (Figure 5(d)). All dogs in the no oral mass group had a CRP level of less than 10 mg/L, which is under the normal range or less than 20 mg/L. In the oral mass group, the median CRP level was 12.45 mg/L and the range was between less than 10 mg/L and28.2 mg/L. In clinical stage I and II, most dogs had CRP levels of less than 10 mg/L. They had the CRP level higher than 20 mg/L in clinical stage II. Most of the dogs in the metastasis group (clinical stage IV) had a plasma CRP level higher than 50 mg/L which is higher than the normal range. The median plasma CRP concentrations of the oral mass group and the metastasis group were 12.45 and 112 mg/L, respectively, and were significantly higher than those of the no oral mass group () (Figure 5(e), Table 5). Also, the CRP levels of the metastasis group were significantly higher than those of the oral mass group () (Figure 5(e) and Table 5). However, one dog in the metastasis group received a nonsteroidal anti-inflammatory drug before the blood collection, and the CRP level of this dog was less than 10 mg/L. So, the CRP level and CAR data of this dog were not included for the statistical analysis. The median CRP and CAR in the oral mass group and the metastasis group were significantly higher than in the no oral mass group () (Figures 5(e) and 5(f) and Table 5). The median CRP of the metastasis group was about 10 times higher than that of the no oral mass group. In addition, the median of the CAR of the oral mass and metastasis groups was higher than that of the no oral mass group about 10–15 times and 100 times, respectively.

(a)

(b)

(c)

(d)

(e)

(f)

3.3. Bacterial Isolation and Identification

Among a total of 36 oral swab samples, 77 bacterial isolates were analyzed based on 16S rRNA gene taxonomy (Table 7) (Supplementary file 1-2). There were four bacterial phyla: Proteobacteria (51/77, 66.23%), Firmicutes (22/77, 28.57%), Actinobacteria (3/77, 3.70%), and Bacteroidetes (1/77, 1.30%). Proteobacteria was the majority phylum of isolated bacteria in all groups: the no oral mass group (31/46, 67.39%), the oral mass group (10/16, 62.50%), and the metastasis group (10/15, 64.52%) (Figure 6). In our study, there were nine families in the Proteobacteria: Rhodobacteraceae, Neisseriaceae, Alcaligenaceae, Aeromonadaceae, Enterobacteriaceae, Morganellaceae, Pasteurellaceae, Moraxellaceae, and Pseudomonadaceae. Pasteurellaceae (14/46, 30.43%) and Neisseriaceae (13/46, 28.26%) were the two main bacterial families in the no oral mass group (Figure 7). We found that the bacterial isolates of family Pasteurellaceae in the oral mass group (Fisher’s exact = 6.807, ) (OR = 0.071, 95%CI: 0.007–0.70, ) and the metastasis group (Fisher’s exact = 5.79, ) (OR = 0.083, 95%CI: 0.008–0.833, ) were significantly lower than the no oral mass group. Moreover, the bacterial isolates of the Neisseriaceae family in the clinical groups showed a lower trend than in the no oral mass group (Fisher’s exact = 6.39, , borderline significance). Interestingly, Enterobacteriaceae was the majority bacterial family of both clinical cases groups, which were the oral mass group (4/16, 25%) and the metastasis group (5/15, 33.33%) (Figure 7). This family was not isolated from the no oral mass group. From our result, the bacterial isolates of Enterobacteriaceae family showed the higher evidence in the oral mass group (Fisher’s exact = 12.18, ) and the metastasis group (Fisher’s exact = 18.26, ) compared with the no oral mass group. Also, the bacterial isolates of Alcaligenaceae, Aeromonadaceae, Enterococcaceae, and Corynebacteriaceae families were identified from the two clinical case groups (Figure 7).

In the present study, the bacterial isolates were identified into 20 genera: Frederiksenia spp., Paracoccus spp., Providencia spp., Gemella spp., Rothia spp., Neisseria spp., Pasteurella spp., Staphylococcus spp., Streptococcus spp., Moraxella spp., Pseudomonas spp., Elizabethkingia spp., Achromobacter spp., Aeromonas spp., Acinetobacter spp., Klebsiella spp., Enterococcus spp., Corynebacterium spp., Escherichia spp., and Shigella spp. (Figure 8). The three main bacterial genera in all groups were Neisseria spp. (16/77, 20.78%), Staphylococcus spp. (13/77, 16.88%), and Pasteurella spp. (11/77, 14.29%). Interestingly, Neisseria spp. was the main genus of bacterial isolates from all the groups. In the no oral mass group, the three majority genera of bacterial isolates were Neisseria spp. (13/46, 28.26%), Pasteurella spp. (9/46, 19.57%), and Staphylococcus spp. (9/46, 19.57%). Bacterial isolates from the genus Frederiksenia spp., Paracoccus spp., Providencia spp., Gemella spp., and Rothia spp. were found only in the no oral mass group (Figure 8).

In the oral mass group, there were four main genera of bacterial isolates: Neisseria spp. (2/16, 12.5%), Staphylococcus spp. (2/16, 12.5%), Klebsiella spp. (2/16, 12.5%), and Escherichia spp. (2/16, 12.5%). Pasteurella spp., Streptococcus spp., Elizabethkingia spp., Achromobacter spp., Aeromonas spp., Acinetobacter spp., Enterococcus spp., and Corynebacterium spp. were also isolated from the oral mass group. In the metastasis group, the three main majority genera of bacterial isolates were Escherichia spp. (4/15, 26.67%), Pseudomonas spp. (2/15, 13.33%), and Staphylococcus spp. (2/15, 13.33%). Aeromonas spp., Acinetobacter spp., Klebsiella spp., and Shigella spp. were also isolated from the metastasis group. There were three genera of bacterial isolates which were Enterococcus spp., Corynebacterium spp., and Escherichia spp. found in both the clinical groups (Figure 8). Moreover, Shigella spp. was isolated from only the metastasis group. Based on our results, Neisseria spp. isolates decreased in the clinical groups (Fisher’s exact = 6.39, , borderline significance). Interestingly, Escherichia spp. was found in samples from the clinical groups, and we did not find evidence of this genus in the no oral mass group. This difference between the no oral mass group and the clinical groups was confirmed to have statistical significance (Fisher’s exact = 12.857, ). Escherichia spp. showed significantly higher evidence in the metastasis group (Fisher’s exact = 14.00, ) compared with the no oral mass group. Finally, the summary figure of the animal groups, the sample collections, and the interesting results of this study were provided in Figure 9.

4. Discussion

The present study aimed to compare blood profiles and plasma CRP levels among the no oral mass group and the two clinical groups. Both the clinical groups, the oral mass group and the metastasis group, showed a significant decrease in total RBC when compared with the no oral mass group. This finding may imply that most of the severe tumor-bearing dogs showed the anemia status which is related to the mass bleeding. Moreover, the growing mass in the oral cavity may have interfered with the dog’s nutrition consumption. This status relates to the anemia of inflammatory disease (AID) which is the mild to moderate severity, nonregenerative anemia in chronic diseases including the neoplasia [49]. Previous reports have claimed that inflammation plays a key role in this type of anemia. Shortening RBC life span, impaired erythropoietin-mediated erythropoiesis, and inhibition of iron metabolism are the clinicopathological features [49]. The point is that if the oral mass cannot be treated, alternative treatments should be performed for these dogs such as blood transfusion in severe anemia cases, parenteral iron therapy, and the administration of recombinant human erythropoietin in mild to moderate anemic dogs.

According to the CBC results, there was a trend toward increasing WBC and the NLR in the oral mass group and the metastasis group compared to the no oral mass group. This implies that the tumor-bearing group displayed the inflammation feature. Many bacterial isolates in our study were the gram-negative bacteria. Gram-negative bacteria and their endotoxins, lipopolysaccharide (LPS), play the important role of inflammatory stimuli that are activated through the inflammatory cytokines [46, 50]. In addition, lipoteichoic acid (LTA) of Gram-positive bacteria is also one of the antigens that activated the immune cells [34]. The chronic inflammation, loss of surface integrity in the oral mucosal epithelium, and structure of the oral cancer in patients may result from the persistent bacterial colonization of mucosa or cancer epithelial cells, which has been observed at various stages of oral cancer. Thus, chronic inflammation could result from persistent mucosal or epithelial cell colonization by microorganisms. There is a lot of evidence of oral bacteria that are involved in the inflammation [2, 46, 51].

In this study, the CRP level of both the clinical groups was significantly higher than those of the no oral mass group and the increasing of the CRP level was related to the severity clinical stage. Cancer and inflammation are associated in a way that some cancers arise at the sites whereas the cancer induces an inflammatory microenvironment. We could support that CRP is a sensitive marker that has been shown to increase in response to malignancies [19, 26] such as lymphoma [18, 52], multiple myeloma [53], pancreatic cancer [54], and SCC [55]both in humans and dogs. In most studies, CRP levels were found to be highly elevated in patients with cancer and metastasis compared with the healthy control group or benign conditions [26, 27, 56]. These CRP-related inflammatory evidence may be the potential role of the tissue injuries which related to the tumor consequence of inflammatory response. The role of inflammation in the tumor development and progression was mentioned and added to the new version of hallmarks of cancer in human by Hanahan [45].

One dog with oral malignant melanoma that had regional lymph node and lung metastasis (clinical stage IV) and a plasma CRP level of 115 mg/L, died within seven days of the first visit. Increasing CRP levels and blood profiles showed a severe leukocytosis inflammatory pattern. The critical CRP value was mentioned in the systemic inflammatory response or severe emergency cases [24, 27]. According to our results, the CRP level in a high clinical stage presented as greater than 100 mg/L, as in previous studies. Elevated CRP is likely a response secondary to tumor necrosis and local tissue damage; this response may be attributable to bacterial translocation from the damaged oral mucosa, endothelium, and resulting septicemia that is associated with inflammation in patients with malignancies. NSAIDs inhibit the cyclooxygenase enzymes and anti-inflammation [57]. NSAIDs were the clinical factor for the dog that had a CRP level in the normal range.

In the oral mass with the metastasis group, the CRP and ALKP enzyme levels were significantly high. It is a fact that hepatocytes are the main cells that produce and release CRP to the systemic circulation. This process occurs in response to increased levels of circulating proinflammatory cytokines [58, 59]. Therefore, the plasma CRP and ALKP levels may be correlated with proinflammatory mediators, especially interleukin-1 (IL-1) and interleukin-6 (IL-6) in liver cells [58–60]. There are three isoforms of ALKP: liver ALKP (LALKP), bone ALKP (BALKP), and corticosteroid-induced ALKP (CALKP). ALKP is the primary indicator of cholestatic liver disease. This enzyme also increases with severe bone destruction and steroid induction. The increase in BALKP, which is shown in the total ALKP, is usually found in young puppies or during times of active osteoblast and bone development [61]. In our study, the metastasis dogs had increased ALKP levels. Their abdominal ultrasound examination results did not show any alteration of the liver and/or bile duct structure. The alteration of bone or bone lytic condition due to the cancer metastasis may be the cause of the increasing ALKP level in the malignant part with metastasis group compared to the no oral mass group and the oral mass without metastasis group. However, we cannot conclude that the total ALKP increase is due to bone destruction. In the future, a specific method for BALKP detection should be performed for the exact BALKP level, and then we can know the source of ALKP that is increasing in metastasis cases [62].

We compared the clinical blood results between the no oral mass group and the tumor-bearing groups and found that the plasma ALB levels and the AGR in the two clinical groups, the oral mass group and the metastasis group, were significantly lower than in the no oral mass group. Conversely, the GLOB and the GAR in the clinical groups were significantly higher than in the normal group. In addition, the CAR was significantly higher in the clinical groups compared to the normal group. These results, like those in previous studies, showed that both hypoalbuminemia and the elevated CRP concentration were associated with malignancy and related to survival time [26]. In our study, NLR was also evaluated as biomarker of a systemic inflammatory response. Both clinical groups showed an increasing trend. This finding was related with the previous study in dogs with gingivitis and dogs with oropharyngeal tumors [63]. The predictive ability for patients with advanced cancers might be improved by combining CRP with other parameters, such as plasma albumin and NLR.

In human medicine, the oral microbiomes of diseases and healthy people are different from those of dogs according to the sequencing method [30]. Therefore, there seem to be considered differences between the oral microbiomes of the different species [31, 33, 47, 64, 65]. This study aimed to identify oral bacterial samples from dogs with no oral mass and clinical oral tumor-bearing dogs. We focused on the cultivable bacteria living in the oral mucosal surface of dogs. To this point, the assembly of the 16S rRNA gene of bacterial isolates provides a new view of the oral bacterial profile in the canine oral tumor-bearing group compared with the no oral mass group. Traditionally, bacterial identification in laboratories was performed using phenotypic tests, including Gram smear and biochemical tests, considering culture requirements and growth characteristics [66, 67]. However, these methods of bacterial identification have major limitations due to the phenotypic tests and biochemical tests. Nowadays, the modern PCR, automated DNA sequencing, and work on 16S rDNA sequencing bacteria can make an accurate identification of bacterial isolates. From this point, the accurate identification is one of the most important functions of clinical microbiology laboratories and solves the problem related to the traditional method [66, 68–70].

According to our results, the phylum Proteobacteria was the most abundant bacteria, as reported in previous studies [30, 33, 64]. In our study, Pasteurellaceae and Neisseriaceae were the two main bacterial families in the no oral mass group. The three majority genera of bacterial isolates were Neisseria spp., Pasteurella spp., and Staphylococcus spp. These three bacterial genera can usually be cultured from dog bite wounds in human [71, 72]. This point is related to the previous studies stating that Neisseria spp., including N. canis, N. animaloris, N. dumasiana, N. zoodegmatis, and N. weaverii, are one of the normal floras of dogs [71]. In addition, Pasteurella spp. and Staphylococcus spp. were also isolated as cultivable oral microbial in domestic dogs, but they were related to dental plaque samples in previous studies [29, 32]. In this study, Enterobacteriaceae was the majority bacterial family in both the clinical case groups. Escherichia spp. and Shigella spp. were not isolated from the dogs in the no oral mass group. Moreover, Neisseria spp. and Pasteurella spp. decreased in both oral mass groups. In addition, the bacteria in the genera Aeromonas spp., Acinetobacter spp., Elizabethkingia spp., Klebsiella spp., Enterococcus spp., Corynebacterium spp., and Escherichia spp. were found in the oral mass group. This alteration in oral bacterial isolation is may be due to the changes in the oral microenvironment that destroy the normal microbial population and conduct the opportunistic microorganisms to increase the population. The unique microbial profile in humans with SCC is different from the normal humans [36]. The discovery of bacterial replication in the tumor may be linked to the presence of bacterial nutrients and chemotactic compounds. Moreover, the alteration in the salivary microbiome of pancreatic cancer patients compared to the healthy control group empathized with those hypotheses. The researchers attempted to select the human oral microbiome as the noninvasive method for the diagnosis of the oral and gastrointestinal cancer. Recently, the researchers discovered the relationship of the dysbiosis of bacteria in gut and oral bacteria in dogs. In that study, the Bacteroides bacteria were shared in the intratumoral, oral, and gut bacterium community of canine mammary tumor cases. This result confirmed that these bacteria might travel from the gastrointestinal tract to the tumor sites [73]. This was related to previous study in human oral SCC and the bacterial translocation. They isolated the enteric bacteria such as Klebsiella, Enterobacter, and Enterococcus from the tissue of oral mass and regional lymph node before surgery and the infection of sites after operation [74]. In addition, the patients with malignant cancers are more susceptible to get infected by the pathogenic bacteria in comparison to benign patients [75]. Thus, based on our results, the alteration of the oral microbial profile and the bacterial translocation in the canine oral tumor-bearing group is an interesting point for further study related to the diagnosis and prediction of canine oral cancer.

Oh et al. reported that Porphyromonas, Fusobacterium, Actinomyces, Neisseria and Pasteurella were the most abundant genera of the bacterial swab from the buccal area and the supragingival plaque [30, 33]. According to the several distinct microbial habitats and the oral cavity area, the tongue is the most populated niche, and this area has an impact on other regions in the oral cavity. The tongue and saliva facilitated the bacteria to travel around the oral cavity [50]. Ruparella et al. and team reported that saliva exhibited the lowest bacterial diversity, the buccal and the tongue dorsum mucosa had the most similar bacteria [33]. Moreover, the teeth area and the dental plaque were the selected area for the periodontal disease [31, 32, 67, 70, 76–78]. So, the oral swab sample from the tongue’s dorsum mucosa and the mucosa of the hard palate of each dog was taken to compare the microbes among the three groups of dogs in our study. This site of the sampling method showed the microbe profiles that differ from the previous study that interested in the buccal site and supragingival plaque. According to our study, the bacteria from the supragingival plaque that is related to the periodontitis might not interfere with the results of bacterial isolates in our samples. Many oral bacteria are slow growing, require complex culture media, and specific atmospheric requirements [69, 70, 79]. However, many bacterial species could not be cultured in this study because they are difficult to reproduce under laboratory conditions. Oral anaerobic bacteria such as Porphyromonas spp., Fusobacterium spp., Bacteriodes spp., Capnocytophaga spp., Prevotella spp., Tannerella spp., Treponema spp., and Actinomyces spp. reported in the previous study [29, 31, 48, 70, 77, 79, 80] were not found in our study. Some bacterial isolates have been detected from the environment, as the channel of a dog’s mouth is exposed to the outdoor environment.

In veterinary medicine, there have been few reports about canine oral microbiomes with malignancies. The present study investigated oral microbial isolates in canines bearing oral tumor and compared the oral microbial isolates and blood clinical profiles among the no oral mass group and the clinical groups. Most frequently, isolates were normal oral flora which were not considered primary pathogens in the no oral mass group. The alterations in canine oral bacteria with oral mass compared to healthy dogs in this study may be related to microbiome alteration and dysbiosis. This suggested that bacteria may play the same potential roles in the pathogenesis and cancer progression of oral cancer as inflammatory pathogens in human. These were mentioned in the review article by Faden that there are many mechanisms including (a) chronic infection altered cell growth, (b) infection resulting in suppression of apoptosis, (c) chronic infection induced cell proliferation and DNA replication, (d) bacterial products caused the epithelial DNA damage and secondary hyper-proliferative epithelium, and (e) carcinogenic nitrosamine produced by E. coli linked to oral cancer development [51].

We focused on identifying cultivable bacteria living in the oral mucosal surface of dogs with the culture-based method and 16s rRNA gene sequencing. We obtained a lower number of bacterial colonies compared to recent reports using advance sequencing methods [30, 33]. However, our results did not interfere by the DNA component of dead bacteria that can be detected by the advance sequencing methods in the previous studies [34]. The most abundant bacterial phyla from the oral swab in this study were not similar as the study of McDonald et al. [81] and Dewhirst et al. [47]. Our data was similar to the study of Ruparell et al.[33]; this may be the result of the site of sample collection and the sample preparation for bacterial identification. The direct oral swab samples for next generation sequencing (NGS) or the whole genome sequencing (WGS) provided the bacterial taxonomies more than the culture based and 16s RNA gene sequencing method and those methods could detect the uncultured bacteria [62–64]. Furthermore, the different settings of the disease groups, sample collection between awakening dogs and those under anesthesia, could be a confounding factor leading to different results [82]. Limitations of this study were the small numbers of dogs in each group, the different tumor types within the tumor bearing-dog groups and the cultured bacterial isolate-based method. Due to the limitations of this study, we suggest that the number of samples should be increased to provide more interesting and valuable information for the further study.

5. Conclusion

This study provides the knowledge of the oral bacterial population from the culture-based with 16s rRNA gene sequencing method that points toward the role of bacterial alteration and tumor-promoting inflammation. Canine oral cancers have a poor prognosis and are related to the chronic status which may decrease the host oral mucosa immunity and increase the risk of secondary bacterial infection. We compared the bacterial isolates and blood profiles of dogs in the three groups. Significantly, both clinical groups showed anemia, an increase in NLR, GAR, CRP, and CAR, and a decrease in AGR compared to the normal group. Neisseria spp. was the main genus of bacterial isolates in the oral swabs. Interestingly, Neisseria spp. decreased in the clinical groups, and Escherichia spp. increased in the clinical groups. Our results on the differences of the oral bacteria among the groups of dogs and the increase in the CRP, CAR, and NLR suggest that the bacteria and the oral cancer may be related and play a potential role in cancer progression. Whether or not bacterial play the role in tumorigenesis and progression, it is an interesting point to further explore the effect that the bacteria may have on different phenotypes of cancer cells and their interactions with the cancer cells. Thus, further studies may provide the new knowledge in this field and/or facilitate the new treatment options. The studies should be conducted on the larger sample size and investigate the correlation between the specific bacteria, the type of canine oral mass, the clinical blood profiles, and the clinical stage of oral cancer.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Authors’ Contributions

Setthawongsin C., Meekhanon N., and Rungsipipat A. contributed to conceptualization and methodology. Pisamai S., Rungsipipat A., and Setthawongsin C. were involved with sample and data collection. Khunbutsri D., Rungsipipat A., and Setthawongsin C. were involved in investigation and laboratory work. Jarudecha T. and Setthawongsin C. were involved with the data validation and statistical analysis. Setthawongsin C. was responsible for writing original draft. Ngamkala S., Raksajit W., Meekhanon N., Rungsipipat A., and Setthawongsin C., contributed to writing the original draft and graph presentation. Rungsipipat A. was involved in research supervision. All the authors reviewed and provided critical comments on the manuscript and read and approved the final version of the manuscript.

Acknowledgments

The authors gratefully acknowledge generous funding from Kasetsart UniversityResearch and Development Institute (KURDI), Bangkok, Thailand. C. Setthawongsin and W. Raksajit were supported by the Faculty of Veterinary Technology, Kasetsart University, Bangkok, Thailand, and Research and Development Institute (KURDI), FF (KU) 38.65.

Supplementary Materials

Supplementary file 1: the nucleotide sequences of bacterial isolates from the no oral mass dogs. Supplementary file 2: the nucleotide sequences of bacterial isolates from the dogs with oral mass. (Supplementary Materials)

References

D. M. Vail and E. G. MacEwen, “Spontaneously occurring tumors of companion animals as models for human cancer,” Cancer Investigation, vol. 18, no. 8, pp. 781–792, 2000.
View at: Publisher Site | Google Scholar
Q. Li, Y. Hu, X. Zhou, S. Liu, Q. Han, and L. Cheng, “Role of oral bacteria in the development of oral squamous cell carcinoma,” Cancers, vol. 12, no. 10, p. 2797, 2020.
View at: Publisher Site | Google Scholar
S. L. Goldschmidt, C. M. Bell, S. Hetzel, and J. Soukup, “Clinical characterization of canine acanthomatous ameloblastoma (CAA) in 263 dogs and the influence of postsurgical histopathological margin on local recurrence,” Journal of Veterinary Dentistry, vol. 34, no. 4, pp. 241–247, 2017.
View at: Publisher Site | Google Scholar
K. Yoshida, T. Yanai, T. Iwasaki et al., “Clinicopathological study of canine oral epulides,” Journal of Veterinary Medical Science, vol. 61, no. 8, pp. 897–902, 1999.
View at: Publisher Site | Google Scholar
L. B. Brønden, T. Eriksen, and A. T. Kristensen, “Oral malignant melanomas and other head and neck neoplasms in Danish dogs - data from the Danish Veterinary Cancer Registry,” Acta Veterinaria Scandinavica, vol. 51, no. 1, p. 54, 2009.
View at: Publisher Site | Google Scholar
S. Komazawa, H. Sakai, Y. Itoh et al., “Canine tumor development and crude incidence of tumors by breed based on domestic dogs in Gifu prefecture,” Journal of Veterinary Medical Science, vol. 78, no. 8, pp. 1269–1275, 2016.
View at: Publisher Site | Google Scholar
D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell, vol. 144, no. 5, pp. 646–674, 2011, https://doi.org/10.1016/j.cell.2011.02.013.
View at: Google Scholar
T. Shida, T. Kuribayashi, T. Seita, T. Maruo, and S. Yamamoto, “Characteristics of c-reactive protein (CRP), a1-acid glycoprotein (AAG) and serum amyloid a (SAA) in dogs and cats with malignant cancer,” International Journal of Applied Research in Veterinary Medicine, vol. 9, no. 4, pp. 376–381, 2011.
View at: Google Scholar
A. E. Jergens, C. A. Schreiner, D. E. Frank et al., “A scoring index for disease activity in canine inflammatory bowel disease,” Journal of Veterinary Internal Medicine, vol. 17, no. 3, pp. 291–297, 2003.
View at: Publisher Site | Google Scholar
C. S. Mansfield, F. E. James, and I. D. Robertson, “Development of a clinical severity index for dogs with acute pancreatitis,” Journal of the American Veterinary Medical Association, vol. 233, no. 6, pp. 936–944, 2008, https://doi.org/10.2460/javma.233.6.936.
View at: Google Scholar
K. W. Seo, J. B. Lee, J. O. Ahn et al., “C-reactive protein as an indicator of inflammatory responses to experimentally induced cystitis in dogs,” Journal of Veterinary Science, vol. 13, no. 2, pp. 179–185, 2012.
View at: Publisher Site | Google Scholar
M. B. Christensen, R. Langhorn, A. Goddard et al., “Comparison of serum amyloid A and C-reactive protein as diagnostic markers of systemic inflammatio.n in dogs,” Canadian Veterinary Journal, vol. 55, no. 2, pp. 161–168, 2014.
View at: Google Scholar
M. Kocaturk, A. Tvarijonaviciute, S. Martinez-Subiela et al., “Inflammatory and oxidative biomarkers of disease severity in dogs with parvoviral enteritis,” Journal of Small Animal Practice, vol. 56, no. 2, pp. 119–124, 2015.
View at: Publisher Site | Google Scholar
M. E. Mylonakis, J. J. Ceron, L. Leontides et al., “Serum acute phase proteins as clinical phase indicators and outcome predictors in naturally occurring canine monocytic ehrlichiosis,” Journal of Veterinary Internal Medicine, vol. 25, no. 4, pp. 811–817, 2011.
View at: Publisher Site | Google Scholar
S. J. Viitanen, A. K. Lappalainen, M. B. Christensen, S. Sankari, and M. M. Rajamäki, “The utility of acute-phase proteins in the assessment of treatment response in dogs with bacterial pneumonia,” Journal of Veterinary Internal Medicine, vol. 31, no. 1, pp. 124–133, 2017.
View at: Publisher Site | Google Scholar
S. J. Viitanen, H. P. Laurila, L. I. Lilja-Maula, M. A. Melamies, M. Rantala, and M. M. Rajamäki, “Serum C-reactive protein as a diagnostic biomarker in dogs with bacterial respiratory diseases,” Journal of Veterinary Internal Medicine, vol. 28, no. 1, pp. 84–91, 2014.
View at: Publisher Site | Google Scholar
F. Tecles, M. Caldín, A. Zanella et al., “Serum acute phase protein concentrations in female dogs with mammary tumors,” Journal of Veterinary Diagnostic Investigation, vol. 21, no. 2, pp. 214–219, 2009.
View at: Publisher Site | Google Scholar
F. Tecles, E. Spiranelli, U. Bonfanti, J. J. Cerón, and S. Paltrinieri, “Preliminary studies of serum acute-phase protein concentrations in hematologic and neoplastic diseases of the dog,” Journal of Veterinary Internal Medicine, vol. 19, no. 6, pp. 865–870, 2005.
View at: Publisher Site | Google Scholar
V. Mukorera, E. Dvir, L. L. van der Merwe, and A. Goddard, “Serum C-reactive protein concentration in benign and malignant canine spirocercosis,” Journal of Veterinary Internal Medicine, vol. 25, no. 4, pp. 963–966, 2011.
View at: Publisher Site | Google Scholar
K. H. Allin and B. G. Nordestgaard, “Elevated C-reactive protein in the diagnosis, prognosis, and cause of cancer,” Critical Reviews in Clinical Laboratory Sciences, vol. 48, no. 4, pp. 155–170, 2011.
View at: Publisher Site | Google Scholar
P. Póvoa, L. Coelho, E. Almeida et al., “C-reactive protein as a marker of infection in critically ill patients,” Clinical Microbiology and Infection, vol. 11, no. 2, pp. 101–108, 2005.
View at: Publisher Site | Google Scholar
K. Sasaki, I. Fujita, Y. Hamasaki, and S. Miyazaki, “Differentiating between bacterial and viral infection by measuring both C-reactive protein and 2'-5'-oligoadenylate synthetase as inflammatory markers,” Journal of Infection and Chemotherapy, vol. 8, no. 1, pp. 76–80, 2002.
View at: Publisher Site | Google Scholar
C. Gebhardt, J. Hirschberger, S. Rau et al., “Use of C-reactive protein to predict outcome in dogs with systemic inflammatory response syndrome or sepsis,” Journal of Veterinary Emergency and Critical Care, vol. 19, no. 5, pp. 450–458, 2009.
View at: Publisher Site | Google Scholar
S. Hindenberg, N. Bauer, and A. Moritz, “Extremely high canine C-reactive protein concentrations > 100 mg/l - prevalence, etiology and prognostic significance,” BMC Veterinary Research, vol. 16, no. 1, p. 147, 2020.
View at: Publisher Site | Google Scholar
S. Jitpean, B. S. Holst, O. V. Höglund et al., “Serum insulin-like growth factor-I, iron, C-reactive protein, and serum amyloid A for prediction of outcome in dogs with pyometra,” Theriogenology, vol. 82, no. 1, pp. 43–48, 2014.
View at: Publisher Site | Google Scholar
M. Nakamura, M. Takahashi, K. Ohno et al., “C-reactive protein concentration in dogs with various diseases,” Journal of Veterinary Medical Science, vol. 70, no. 2, pp. 127–131, 2008, https://doi.org/10.1292/jvms.70.127.
View at: Google Scholar
M. Planellas, A. Bassols, C. Siracusa et al., “Evaluation of serum haptoglobin and C-reactive protein in dogs with mammary tumors,” Veterinary Clinical Pathology, vol. 38, no. 3, pp. 348–352, 2009.
View at: Publisher Site | Google Scholar
J. C. Whittemore, B. A. Marcum, D. I. Mawby, M. V. Coleman, T. B. Hacket, and M. R. Lappin, “Associations among albuminuria, C-reactive protein concentrations, survival predictor index scores, and survival in 78 critically ill dogs,” Journal of Veterinary Internal Medicine, vol. 25, no. 4, pp. 818–824, 2011.
View at: Publisher Site | Google Scholar
D. R. Elliott, M. Wilson, C. M. F. Buckley, and D. A. Spratt, “Cultivable oral microbiota of domestic dogs,” Journal of Clinical Microbiology, vol. 43, no. 11, pp. 5470–5476, 2005.
View at: Publisher Site | Google Scholar
C. Oh, K. Lee, Y. Cheong et al., “Comparison of the oral microbiomes of canines and their owners using next-generation sequencing,” PLoS One, vol. 10, no. 7, Article ID e0131468, 2015.
View at: Publisher Site | Google Scholar
V. Özavci, G. Erbas, U. Parin, H. T. Yüksel, and Ş. Kirkan, “Molecular detection of feline and canine periodontal pathogens,” Veterinary and animal science, vol. 8, Article ID 100069, 2019.
View at: Publisher Site | Google Scholar
A. M. Patel, J. V. Vadalia, V. Kumar, P. B. Patel, and D. B. Barad, “Identifying oral bacterial microflora associated with canine dental plaque--a study of 53 canines,” Intas Polivet, vol. 16, no. 2, pp. 391–399, 2015.
View at: Google Scholar
A. Ruparell, T. Inui, R. Staunton, C. Wallis, O. Deusch, and L. J. Holcombe, “The canine oral microbiome: variation in bacterial populations across different niches,” BMC Microbiology, vol. 20, no. 1, p. 42, 2020.
View at: Publisher Site | Google Scholar
D. Nejman, I. Livyatan, G. Fuks et al., “The human tumor microbiome is composed of tumor type-specific intracellular bacteria,” Science, vol. 368, no. 6494, pp. 973–980, 2020.
View at: Publisher Site | Google Scholar
S. Pushalkar, X. Ji, Y. Li et al., “Comparison of oral microbiota in tumor and non-tumor tissues of patients with oral squamous cell carcinoma,” BMC Microbiology, vol. 12, no. 1, p. 144, 2012.
View at: Publisher Site | Google Scholar
S. Pushalkar, S. P. Mane, X. Ji et al., “Microbial diversity in saliva of oral squamous cell carcinoma,” FEMS Immunology and Medical Microbiology, vol. 61, no. 3, pp. 269–277, 2011.
View at: Publisher Site | Google Scholar
B. L. Schmidt, J. Kuczynski, A. Bhattacharya et al., “Changes in abundance of oral microbiota associated with oral cancer,” PLoS One, vol. 9, no. 6, Article ID e98741, 2014.
View at: Publisher Site | Google Scholar
H. Zhao, M. Chu, Z. Huang et al., “Variations in oral microbiota associated with oral cancer,” Scientific Reports, vol. 7, no. 1, Article ID 11773, 2017.
View at: Publisher Site | Google Scholar
S. J. Engle, I. Ormsby, S. Pawlowski et al., “Elimination of colon cancer in germ-free transforming growth factor beta 1-deficient Mice1,” Cancer Research, vol. 62, no. 22, pp. 6362–6366, 2002.
View at: Google Scholar
J. M. Ward, M. R. Anver, D. C. Haines, and R. E. Benveniste, “Chronic active hepatitis in mice caused by Helicobacter hepaticus,” American Journal Of Pathology, vol. 145, no. 4, pp. 959–968, 1994.
View at: Google Scholar
J. V. Newman, T. Kosaka, B. J. Sheppard, J. G. Fox, and D. B. Schauer, “Bacterial infection promotes colon tumorigenesis in Apc(Min/+) mice,” The Journal of Infectious Diseases, vol. 184, no. 2, pp. 227–230, 2001.
View at: Publisher Site | Google Scholar
M. G. Torralba, G. Aleti, W. Li et al., “Oral microbial species and virulence factors associated with oral squamous cell carcinoma,” Microbial Ecology, vol. 82, no. 4, pp. 1030–1046, 2021.
View at: Publisher Site | Google Scholar
T. M. E. Wassenaar, “E. coli and colorectal cancer: a complex relationship that deserves a critical mindset,” Critical Reviews in Microbiology, vol. 44, no. 5, pp. 619–632, 2018.
View at: Publisher Site | Google Scholar
L. E. Wroblewski, R. M. Peek Jr., and K. T. Wilson, “Helicobacter pylori and gastric cancer: factors that modulate disease risk,” Clinical Microbiology Reviews, vol. 23, no. 4, pp. 713–739, 2010.
View at: Publisher Site | Google Scholar
D. Hanahan, “Hallmarks of cancer: new dimensions,” Cancer Discovery, vol. 12, no. 1, pp. 31–46, 2022.
View at: Publisher Site | Google Scholar
Z. B. Kurago, A. Lam-ubol, A. Stetsenko, C. De La Mater, Y. Chen, and D. V. Dawson, “Lipopolysaccharide-squamous cell carcinoma-monocyte interactions induce cancer-supporting factors leading to rapid STAT3 activation,” Head and Neck Pathology, vol. 2, no. 1, pp. 1–12, 2008.
View at: Publisher Site | Google Scholar
F. E. Dewhirst, E. A. Klein, E. C. Thompson et al., “The canine oral microbiome,” PLoS One, vol. 7, no. 4, Article ID e36067, 2012.
View at: Publisher Site | Google Scholar
J. P. de Carvalho, M. C. Carrilho, D. S. dos Anjos, C. D. Hernandez, L. Sichero, and M. L. Z. Dagli, “Unraveling the risk factors and etiology of the canine oral mucosal melanoma: results of an epidemiological questionnaire, oral microbiome analysis and investigation of papillomavirus infection,” Cancers, vol. 14, no. 14, p. 3397, 2022.
View at: Publisher Site | Google Scholar
C. Chervier, J. L. Cadoré, M. I. Rodriguez-Piñeiro, B. L. Deputte, and L. Chabanne, “Causes of anaemia other than acute blood loss and their clinical significance in dogs,” Journal of Small Animal Practice, vol. 53, no. 4, pp. 223–227, 2012.
View at: Publisher Site | Google Scholar
Y. Lim, M. Totsika, M. Morrison, and C. Punyadeera, “Oral microbiome: a new biomarker reservoir for oral and oropharyngeal cancers,” Theranostics, vol. 7, no. 17, pp. 4313–4321, 2017.
View at: Publisher Site | Google Scholar
A. A. Faden, “The potential role of microbes in oncogenesis with particular emphasis on oral cancer,” Saudi Medical Journal, vol. 37, no. 6, pp. 607–612, 2016.
View at: Publisher Site | Google Scholar
L. Nielsen, N. Toft, P. D. Eckersall, D. J. Mellor, and J. S. Morris, “Serum C-reactive protein concentration as an indicator of remission status in dogs with multicentric lymphoma,” Journal of Veterinary Internal Medicine, vol. 21, no. 6, pp. 1231–1236, 2007.
View at: Publisher Site | Google Scholar
H. Murakami, S. Takada, N. Hatsumi et al., “Multiple myeloma presenting high fever and high serum levels of lactic dehydrogenase, CRP, and interleukin-6,” American Journal of Hematology, vol. 64, no. 1, pp. 76-77, 2000.
View at: Publisher Site | Google Scholar
F. J. Engelken, V. Bettschart, M. Q. Rahman, R. W. Parks, and O. J. Garden, “Prognostic factors in the palliation of pancreatic cancer,” European Journal of Surgical Oncology, vol. 29, no. 4, pp. 368–373, 2003.
View at: Publisher Site | Google Scholar
T. Nozoe, D. Korenaga, M. Futatsugi, H. Saeki, Y. Maehara, and K. Sugimachi, “Immunohistochemical expression of C-reactive protein in squamous cell carcinoma of the esophagus - significance as a tumor marker,” Cancer Letters, vol. 192, no. 1, pp. 89–95, 2003.
View at: Publisher Site | Google Scholar
C. S. Wang and C. F. Sun, “C-reactive protein and malignancy: clinico-pathological association and therapeutic implication,” Chang Gung Medical Journal, vol. 32, no. 5, pp. 471–482, 2009.
View at: Google Scholar
M. S. Bergh and S. C. Budsberg, “The coxib NSAIDs: potential clinical and pharmacologic importance in veterinary medicine,” Journal of Veterinary Internal Medicine, vol. 19, no. 5, pp. 633–643, 2005.
View at: Publisher Site | Google Scholar
H. Murata, N. Shimada, and M. Yoshioka, “Current research on acute phase proteins in veterinary diagnosis: an overview,” The Veterinary Journal, vol. 168, no. 1, pp. 28–40, 2004.
View at: Publisher Site | Google Scholar
K. Yamashita, T. Fujinaga, T. Miyamoto, M. Hagio, Y. Izumisawa, and T. Kotani, “Canine acute phase response: relationship between serum cytokine activity and acute phase protein in dogs,” Journal of Veterinary Medical Science, vol. 56, no. 3, pp. 487–492, 1994.
View at: Publisher Site | Google Scholar
M. F. Thompson, A. L. Litster, J. L. Platell, and D. J. Trott, “Canine bacterial urinary tract infections: new developments in old pathogens,” The Veterinary Journal, vol. 190, no. 1, pp. 22–27, 2011.
View at: Publisher Site | Google Scholar
M. Syakalima, M. Takiguchi, J. Yasuda, and A. Hashimoto, “The age dependent levels of serum ALP isoenzymes and the diagnostic significance of corticosteroid-induced ALP during long-term glucocorticoid treatment,” Journal of Veterinary Medical Science, vol. 59, no. 10, pp. 905–909, 1997.
View at: Publisher Site | Google Scholar
R. A. Sternberg, H. C. Pondenis, X. Yang et al., “Association between absolute tumor burden and serum bone-specific alkaline phosphatase in canine appendicular osteosarcoma,” Journal of Veterinary Internal Medicine, vol. 27, no. 4, pp. 955–963, 2013.
View at: Publisher Site | Google Scholar
A. Rejec, J. Butinar, J. Gawor, and M. Petelin, “Evaluation of complete blood count indices (NLR, PLR, MPV/PLT, and PLCRi) in healthy dogs, dogs with periodontitis, and dogs with oropharyngeal tumors as potential biomarkers of systemic inflammatory response,” Journal of Veterinary Dentistry, vol. 34, no. 4, pp. 231–240, 2017.
View at: Publisher Site | Google Scholar
D. Gopinath, R. K. Menon, C. C. Wie et al., “Differences in the bacteriome of swab, saliva, and tissue biopsies in oral cancer,” Scientific Reports, vol. 11, no. 1, p. 1181, 2021.
View at: Publisher Site | Google Scholar
F. E. Dewhirst, E. A. Klein, M. L. Bennett, J. M. Croft, S. J. Harris, and Z. V. Marshall-Jones, “The feline oral microbiome: a provisional 16S rRNA gene based taxonomy with full-length reference sequences,” Veterinary Microbiology, vol. 175, no. 2-4, pp. 294–303, 2015.
View at: Publisher Site | Google Scholar
P. C. Woo, S. K. Lau, J. L. Teng, H. Tse, and K. Y. Yuen, “Then and now: use of 16S rDNA gene sequencing for bacterial identification and discovery of novel bacteria in clinical microbiology laboratories,” Clinical Microbiology and Infection, vol. 14, no. 10, pp. 908–934, 2008.
View at: Publisher Site | Google Scholar
I. J. Davis, C. Bull, A. Horsfall, I. Morley, and S. Harris, “The Unculturables: targeted isolation of bacterial species associated with canine periodontal health or disease from dental plaque,” BMC Microbiology, vol. 14, no. 1, p. 196, 2014.
View at: Publisher Site | Google Scholar
P. N. Deo and R. Deshmukh, “Oral microbiome: unveiling the fundamentals,” Journal of Oral and Maxillofacial Pathology: JOMFP, vol. 23, no. 1, pp. 122–128, 2019.
View at: Publisher Site | Google Scholar
M. Kilian, I. L. C. Chapple, M. Hannig et al., “The oral microbiome - an update for oral healthcare professionals,” British Dental Journal, vol. 221, no. 10, pp. 657–666, 2016.
View at: Publisher Site | Google Scholar
J. Kačírová, A. Maďari, R. Mucha et al., “Study of microbiocenosis of canine dental biofilms,” Scientific Reports, vol. 11, no. 1, Article ID 19776, 2021.
View at: Publisher Site | Google Scholar
D. Cobiella, D. Gram, and D. Santoro, “Isolation of Neisseria dumasiana from a deep bite wound infection in a dog,” Veterinary Dermatology, vol. 30, no. 6, p. 556, 2019.
View at: Publisher Site | Google Scholar
W. E. Bailie, E. C. Stowe, and A. M. Schmitt, “Aerobic bacterial flora of oral and nasal fluids of canines with reference to bacteria associated with bites,” Journal of Clinical Microbiology, vol. 7, no. 2, pp. 223–231, 1978.
View at: Publisher Site | Google Scholar
H. H. Zheng, C. T. Du, C. Yu et al., “The relationship of tumor microbiome and oral bacteria and intestinal dysbiosis in canine mammary tumor,” International Journal of Molecular Sciences, vol. 23, no. 18, Article ID 10928, 2022.
View at: Publisher Site | Google Scholar
H. Sakamoto, H. Naito, Y. Ohta et al., “Isolation of bacteria from cervical lymph nodes in patients with oral cancer,” Archives of Oral Biology, vol. 44, no. 10, pp. 789–793, 1999.
View at: Publisher Site | Google Scholar
L. Lin, L. Jia, Y. Fu et al., “A comparative analysis of infection in patients with malignant cancer: a clinical pharmacist consultation study,” Journal of infection and public health, vol. 12, no. 6, pp. 789–793, 2019.
View at: Publisher Site | Google Scholar
B. A. Niemiec, J. Gawor, S. Tang, A. Prem, and J. A. Krumbeck, “The bacteriome of the oral cavity in healthy dogs and dogs with periodontal disease,” American Journal of Veterinary Research, vol. 83, no. 1, pp. 50–58, 2022.
View at: Publisher Site | Google Scholar
P. Sanguansermsri, K. Chairatvit, S. Roytrakul, S. Doungudomdacha, and R. Surarit, “Exploring difference in subgingival microbial communities in dog and human periodontal diseases using DGGE technique,” Thai Journal of Veterinary Medicine, vol. 47, no. 1, pp. 7–14, 2017.
View at: Google Scholar
M. P. Riggio, A. Lennon, D. J. Taylor, and D. Bennett, “Molecular identification of bacteria associated with canine periodontal disease,” Veterinary Microbiology, vol. 150, no. 3-4, pp. 394–400, 2011.
View at: Publisher Site | Google Scholar
M. Maďar, J. Kačírová, A. Maďari, R. Mucha, E. Styková, and R. Nemcová, “Cultivable bacterial diversity of the canine dental plaque as a potential source of bacterial infections,” Acta Veterinaria Brno, vol. 90, no. 2, pp. 171–178, 2021.
View at: Publisher Site | Google Scholar
M. Gołyńska, I. Polkowska, M. Bartoszcze-Tomaszewska, A. Sobczyńska-Rak, and Ł. Matuszewski, “Molecular-level evaluation of selected periodontal pathogens from subgingival regions in canines and humans with periodontal disease,” Journal of Veterinary Science, vol. 18, no. 1, pp. 51–58, 2017.
View at: Publisher Site | Google Scholar
J. E. McDonald, N. Larsen, A. Pennington et al., “Characterising the canine oral microbiome by direct sequencing of reverse-transcribed rRNA molecules,” PLoS One, vol. 11, no. 6, Article ID e0157046, 2016.
View at: Publisher Site | Google Scholar
B. Tress, E. S. Dorn, J. S. Suchodolski et al., “Bacterial microbiome of the nose of healthy dogs and dogs with nasal disease,” PLoS One, vol. 12, no. 5, Article ID e0176736, 2017.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2023 Chanokchon Setthawongsin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

726

Downloads

494

Citations