Exploring Novel Biomarkers Through the Lens of Single Cell Sequencing

Exploring Novel Biomarkers Through the Lens of Single Cell Sequencing

Abstract
The success of personalized medicine depends on reliable biomarkers to guide clinical decision-making. Over the past two decades next-generation sequencing technologies have revolutionized biomarker discovery and testing. However, the use of bulk tissue samples has largely obscured the roles played by individual cells and cell populations in pathogenesis. With the rapid emergence of single-cell technologies we are gradually uncovering these roles and, in the process, are exposing a rich layer of information that can be used to define entirely new classes of biomarkers.
Cell-specific expression of key genes or pathways, cell status and cell-state transitions, as well as cellular compositions of tumor tissues, have all been shown to correlate with patient prognosis or responses to treatments in various cancer types.
For example, we increasingly appreciate the importance of inter and intratumor heterogeneity for drug responses and resistance in cancer. Similarly, we can improve disease monitoring by taking a more comprehensive view at the interplay of dysfunctional and normal cells within tumor tissues. Moreover, single-cell approaches allow us to observe cellular behaviors, such as phenotype switching, which are difficult to detect using bulk sequencing approaches due to absence of genetic markers but are attractive targets for therapeutic interventions.
In this talk, we will present our studies on lung and blood cancer to demonstrate how single cell analysis can be used to identify novel biomarkers for patient stratification in personalized cancer therapy.