Utilization of spatial transcriptomics for uncovering the hypoxic transcriptional landscape of tumors

Many cancer therapies, such as radiation therapy, chemotherapy, and antibody treatments, are ineffective at targeting the hypoxic regions in tumors, leading to poor clinical outcome and increased risk for relapse. To date, good complementary treatment options are lacking.

The transcriptomic landscape of hypoxic regions in tumors is also not known in detail since effective means to measure transcriptome per hypoxia level have previously not been available.

With the arrival of spatial transcriptomics, where spots containing a few or even single cells can be sequenced and given a physical coordinate, this is no longer the case.

In this project, I plan to combine spatial transcriptomics and hypoxia staining, in which each sequenced spot will be assigned a degree of hypoxia, to create a transcriptomic atlas over the hypoxic regions in tumors.

Furthermore, I will employ computational methods, primarily metabolic modeling, to identify drug targets specifically targeting cells in all or parts of these regions.

Drugs exploiting these targets could then be developed and hopefully serve as a complement to existing therapies to increase treatment effectiveness as well as reduce the risk of relapse.