FWF - Antisense - Antisense and Allele-specific Transcription in Human Cancer

Identification of cancer-restricted biomarkers is fundamental to the development of novel cancer therapies and diagnostic/prognostic stratification tools. Antisense transcripts have barely been studied in this regard but are likely to exhibit high potential for such applications. The term antisense transcript usually refers to a capped and polyadenylated transcript, which is at least partially complementary to a corresponding (mainly protein-coding) sense mRNA. These transcripts can have diverse functional roles in gene regulation, such as modifying epigenetic marks. The genomic arrangement of sense/antisense pairs also suggests that antisense transcripts are mainly involved in allele-specific gene regulation. In this project we, Dr. Julia Feichtinger (applicant) and Dr. Christoph Sensen (co-applicant) at Institute of Molecular Biotechnology, Graz University of Technology, propose for the first time an extended approach reaching beyond conducting individual studies on antisense and allele-specific expression. We aim to construct a comprehensive picture of these processes in a large panel of cancer samples and healthy controls by making use of the current wealth of transcriptomics and (epi)genomics data provided in the constantly growing public repositories. To this end, we will apply advanced bioinformatics methods to analyse these datasets in a highthroughput and highly optimised manner to obtain transcriptional resolution on all four DNA strands (both alleles). This is not routinely performed in expression studies and will resolve many, otherwise undetected, confounding results. Our main goal is to characterise the potential of antisense transcripts for clinical applications. The construction of comprehensive profiles to define tissue- and cancer-specific expression and the correlation with patient survival are crucial for this. Thereby, we expect to identify a number of novel candidates for therapeutic, diagnostic and prognostic applications. We aim to investigate antisense transcripts of germline genes in more detail as a model to determine whether antisense expression might be linked to oncogenesis, as a number of these genes are aberrantly expressed in cancer as well as are linked to oncogenesis and prognosis. As we hypothesise that antisense transcripts mainly exhibit allele-specific behaviour, we will investigate to what extent allele-specific expression is associated with antisense transcription. In cancers, allele-specific expression is highly elevated, which is mainly the result of copy number variations or changes in allelic compositions. However, we also hypothesise allele-specific epigenetic regulation to drive allele-specific expression, which in turn could partly be induced by (dysregulated) antisense transcripts. To this end, we will analyse multi-omics datasets to produce comprehensive regulatory associations. We further aim to generate annotation maps for sense/antisense pairs in various cancer and normal tissues, expecting these maps to become a powerful resource for the research community. In conclusion, we will investigate antisense and allele-specific transcription in a large-scale study, which will not only lead to new insights into gene regulation and provide novel diagnostic/prognostic marker and drug target candidates for clinical applications, but could also change the paradigm on how we conduct expression analyses in the future.