SUPR
Discovery of cancer-specific microRNAs from The Cancer Genome Atlas resource
Dnr:

sens2022576

Type:

SNIC SENS

Principal Investigator:

Marc Friedländer

Affiliation:

Stockholms universitet

Start Date:

2022-09-26

End Date:

2024-10-01

Primary Classification:

10610: Bioinformatics and Systems Biology (methods development to be 10203)

Allocation

  • Castor /proj at UPPMAX: 5000 GiB
  • Cygnus /proj at UPPMAX: 5000 GiB
  • Castor /proj/nobackup at UPPMAX: 3000 GiB
  • Cygnus /proj/nobackup at UPPMAX: 3000 GiB
  • Bianca at UPPMAX: 2 x 1000 core-h/month

Abstract

MicroRNAs (miRNAs) are small RNA molecules that regulate the expression of protein-coding genes. They are important in defining cell identity, and thousands of studies link them to various cancer types. miRNAs can originate from any transcript, but a delicate equilibrium of biogenesis proteins ensures that only the correct set of miRNAs is produced in a given cell. My research team has found preliminary evidence that perturbation of this equilibrium can result in human cancer-specific miRNAs that are not present in any healthy tissues. Importantly, current profiling methods are in effect blind to cancer-specific miRNAs since they are not yet annotated. My team will apply our experience in miRNA discovery and annotation to find completely new cancer-specific miRNAs from the extensive database of The Cancer Genome Atlas (TCGA) database. Specifically, we will search data from breast, prostate, lung and colon carcinomas. Complementing with TCGA patient metadata, we can pinpoint new miRNAs that specify cancer subtypes or that have prognostic or diagnostic value. The successful completion of our project would reveal a catalog of new miRNAs specific to four prevalent cancer types. Importantly, these cancer-specific miRNAs would constitute ideal biomarkers and drug targets, since they are absent from healthy tissues. They will thus be unambiguous biomarkers and RNA-based drugs that inhibit them will not interfere with ordinary functions of the miRNAs in healthy tissues. This project is the main PhD project of my student Panagiotis Kalogeropoulos. The project is funded by Cancerfonden with project number 21 1530 Pj. We have already obtained permission to access the sequence data from the TCGA database, however since the data are sensitive, it is essential that we work with them in the secured Bianca/Castor environment.