To generate a local database of microRNA profiling data from different tissues and tumors we started by mining of the public TCGA (the cancer genome atlas) database to include processed microRNA sequencing profiles from 9781 different healthy tissue and tumor samples encompassing all relevant organs. A second dataset was compiled by obtaining unprocessed sequencing data from 2458 samples from the public Sequencing Read Archive (SRA) that we processed ourselves using publicly available software co-developed by the innovation associate during het PhD: sRNAbench. The TCGA dataset was investigated by statistical methods to understand if tissue specificity of microRNA expression could be found and to understand whether tumorigenesis would change tissue expression profiles. By principle component analysis, indeed a number of tissues was found to contain distinctive microRNA expression profiles (Figure 1). By differential expression analysis and machine learning (LASSO) microRNA panels were identified that are specifically expressed in only one or enriched in a limited number of tissues. These organ-microRNA panels were confirmed by analysis of the SRA dataset. Surprisingly the only tissue that showed no tissue specific or enriched microRNAs in these analyses was the lung.
To understand if the tissue specific microRNA panels could be potentially used as reporters of organ problems, the presence of these microRNAs in plasma samples from healthy individuals was assessed by using sequencing data generated in house at VUMC. Indeed a number of organ specific and organ enriched microRNAs were detected in plasma samples (figure 2). This indicates that indeed using plasma or potentially urine as a source for microRNA profiling, organ diseases could be detected by changes in organ specific microRNA panels.
By comparing tumor tissue microRNA profiles with healthy tissue microRNA profiles it was assessed if changes in microRNA profiles were associated with tumorigenesis that could directly lead to cancer detection. Interestingly indeed several tumor tissues, including breast, colon and prostate showed significant changes in microRNAs, but these were not always changes in tissue specific microRNAs.
Overal the results from this project confirm the observations from literature that tissue specific or enriched microRNA panels exist that are found in body fluids. Moreover, changes of expression in microRNA panels were found associated with specific forms of cancer. The discovered cancer-microRNA panels can be used in separation or combination as algorithms for cancer detection in body fluids and it is likely that this can be extended also to the detection of other organ diseases. The absence of a lung or lung cancer enriched microRNA panel could mean that lung cancer detection by this method will be difficult. In literature however, multiple studies have shown the feasibility of lung cancer detection by microRNA panels in blood, indicating that our current panels may be improved and extended with additional data.
Besides indications for the feasibility of multi-organ cancer detection, the building and curating of 2 large databases of tissue-specific microRNA expression profiles has generated a valuable resource for biomarker discovery and validation.
The results of the project are forming the basis for a scientific manuscript that is currently in preparation and is expected to be ready for submission to a peer reviewed journal in 2022.
