| Literature DB >> 31785619 |
Yicheng Wang1, Gang Yang1, Lei You1, Jinshou Yang1, Mengyu Feng1, Jiangdong Qiu1, Fangyu Zhao1, Yueze Liu1, Zhe Cao1, Lianfang Zheng2, Taiping Zhang3,4, Yupei Zhao5.
Abstract
Pancreatic cancer is one of the most lethal malignancies. Recent studies indicated that development of pancreatic cancer may be intimately connected with the microbiome. In this review, we discuss the mechanisms through which microbiomes affect the development of pancreatic cancer, including inflammation and immunomodulation. Potential therapeutic and diagnostic applications of microbiomes are also discussed. For example, microbiomes may serve as diagnostic markers for pancreatic cancer, and may also play an important role in determining the efficacies of treatments such as chemo- and immunotherapies. Future studies will provide additional insights into the various roles of microbiomes in pancreatic cancer.Entities:
Keywords: Chemotherapy; Diagnosis; Microbiomes; Pancreatic cancer
Mesh:
Substances:
Year: 2019 PMID: 31785619 PMCID: PMC6885316 DOI: 10.1186/s12943-019-1103-2
Source DB: PubMed Journal: Mol Cancer ISSN: 1476-4598 Impact factor: 27.401
Fig. 1Microbiomes play important roles in the development and treatment of pancreatic cancer. The blue arrow indicates that microbiome exposure activates inflammation to promote development of pancreatic cancer. The orange arrow shows that the microbiome leads to immune suppression. The green arrow shows that the microbiome influences the effects of cancer treatments. AHL-12, N-acetyl-dodecanoyl homoserine; T2R38, one of the family of bitter receptors; mTOR, mammalian target of rapamycin; LPS, lipopolysaccharide; TLR, Toll-like receptor; AP-1, Activator protein 1; STAT3, Signal transducers and activators of transcription 3; Th1/2, helper T cell 1/2; PD-1, programmed cell death-1; CDD, cytidine deaminase; 2′,2′-difluorodeoxycytidine, gemcitabine; 2′,2′-difluorodeoxyuridine, an inactive form of gemcitabine
Human studies investigating the role of microbiomes in pancreatic cancer
| Study design | Patients or Samples | Content | Conclusion | Refs |
|---|---|---|---|---|
| Case-control study | ·HOMIM: 10 PC & 10 controls | ·16 of 410 bacterial taxa | Significant changes observed in the microbial composition between pancreatic cancer patients and healthy controls. | [ |
| ·qPCR: 28 PC & 27 chronic pancreatitis patients & 28 controls | · | |||
| Meta-analysis | 8 studies of periodontitis or edentulism | RR for periodontitis and PC was 1.74 (95% CI 1.41–2.15] and 1.54 (95% CI 1.16–2.05) for edentulism | Both periodontitis and edentulism appear to be associated with PC, even after adjusting for common risk factors. | [ |
| Prospective cohort study | Blood samples from 405 PC & 416 controls | Antibodies against | Individuals with high levels of antibodies against | [ |
| Case-control study | 16S rRNA of 30 PHC patients and 25 healthy controls | Microbiome diversity of the tongue coat | The microbiota dysbiosis of the tongue coat in PHC patients was identified. | [ |
| Cohort study | Cyst fluid and plasma of suspected PCN | Bacterial 16S DNA copy number and IL-1β | Intracystic bacterial 16S DNA copy number and IL-1β protein quantity were significantly higher in IPMN. | [ |
| Case-control study | Blood samples from 92 PC & 30 gastric cancer & 35 colorectal cancer & 27 controls | IgG antibodies against | Suggested an association between | [ |
| Case-control study | ·16S rRNA gene of 14 PC & 14 controls | PC patients had higher IL-6 and CRP in blood and a higher incidence of | [ | |
| ·Blood samples | ||||
| ·Urea breath test | ||||
| Meta-analysis | Blood samples of 580 PC & 626 controls | The evidence of CagA strain-specific associations is respective. | [ | |
| Meta-analysis | 117 meta-analytical or pooled reports of the association between specific risk factors and PC risk. | [ | ||
| Meta-analysis | 1003 PC & 1754 controls in 8 case-control studies | OR = 1.45 (95% CI: 1.09–1.92) between | [ | |
| Meta-analysis | 2335 patients in 6 studies | AOR = 1.38 (95%CI: 1.08–1.75; | A significant association between | [ |
| Meta-analysis | 1083 PC & 1950 controls in 9 studies | OR = 1.47 (95%CI: 1.22–1.77) between | [ | |
| Nested case-control study | 104 cases randomly selected subjects among 507 developed PC, 262 cases from 730 controls | [ | ||
| Prospective cohort study | 87 PC & 263 controls from residents born from 1921 to 1949 in Malmö, Sweden | No association between | [ | |
| Meta-analysis | 65,155 observations in 3 cohort studies and 6 nested case-control studies | OR = 1.09(95%CI: 0.81–1.47) | The linkage of PC to | [ |
| Prospective cohort study | 19,924 participants including 126 PC | Individuals with Candida-related lesions had a 70 80% excess risk of developing PC. | [ | |
| Population-based cohort study | 34,829 patients from the National Health Insurance system of Taiwan | The risks of pancreatic cancer was significantly higher in the | [ |
AOR, adjusted odds ratio; CagA, cytotoxin-associated gene-A; CI, confidence interval; CRP, C-reactive protein; HOMIM, Human Oral Microbiological Identification Microarrays; Hp, Helicobacter pylori; IgG, Immunoglobulin G; IL, interleukin; IPMN, intraductal papillary mucinous neoplasm; PC, pancreatic cancer; PCN, pancreatic cystic neoplasm; PHC, pancreatic head carcinoma; Porphyromonas gingivalis ATTC 53978, a pathogenic periodontal bacteria; qPCR, Real-time quantitative polymerase chain reaction; RR, relative risk
Fig. 2Microbiomes are involved in the occurrence pancreatic cancer. Microbiomes can lead to development of inflammation, inhibit interactions between macrophages and T cells, and favor Th2 polarization of the T cell response. All of these factors can contribute to the occurrence of pancreatic cancer. GFR, growth factor receptor; TGF-β, transforming growth factor-β; TbR, transforming growth factor-β receptor; TLR, Toll-like receptor; TNF-α, tumor necrosis factor-α; TNFR, tumor necrosis factor receptor