Microbiota in Clinical Samples of Pancreatic Cancer Patients
Project no. 22790 · Status: Kapanmış · 2021
Summary
<p>Pancreatic cancer is a type of cancer with high mortality due to late detection, lack of screening tests that can be used in early diagnosis, and the lack of surgical treatment after diagnosis in most patients, and therefore it is very important to find diagnostic and follow-up biomarkers. Microbiota shape tissue, oral and intestinal cells, maintain tissue integrity, store energy, protect the body against pathogens and contribute to the shaping of host immunity. However, there is a need for studies on the differences between intrapancreatic and oral bacteria in explaining the mechanism of pancreatic cancer and determining the source, function and mechanism of action of bacteria. In our project, we aimed to identify biomarker candidates that can be used in early diagnosis by evaluating both intrapancreatic and salivary microbiota together and revealing the differences/similarities, to show where the bacteria in the pancreas originate from and to explain the effects of changes in microbiota on pancreatic carcinogenesis. In our study, pancreatic tissue samples will be collected from pancreatic cancer patients during routine surgery to investigate intrapancreatic microbiota. Pancreatic tissue resected during routine surgery of distal choledochal tumour patients will be used as a control group. In addition, microbial differences in saliva samples collected from pancreatic cancer patients and healthy volunteers will be evaluated and when a microorganism showing a significant difference between the two groups is detected, it may be a candidate for early diagnosis biomarker. At the same time, the pancreatic tissue and salivary microbiota of the patients will be compared with each other to determine the differences/similarities in the bacterial composition of these samples and to have an idea about the source of bacterial colonisation in the pancreatic tissue. Firstly, DNA isolation will be performed in all samples and 16S rRNA sequence analysis will be performed. Then, the data obtained will be analysed by bioinformatics and statistical methods.</p>