Session 8

Keynote Speaker: Peter Sorger

Program in Therapeutic Science, Harvard Medical School, Boston, USA

Spatial profiling of human tissues for discovery and diagnosis

The effective treatment of cancer and many other diseases is increasingly dependent on a precision approach in which the quantification of molecular features at the level of individual patients is used to guide treatment plans. Currently, cancer diagnosis and staging are performed primarily via direct examination of biopsy and resection specimens by histopathologists. However, these classical methods provide insufficient molecular insight to guide the use of targeted and immunotherapies even when supplemented by knowledge of tumour genotypes. I will describe the recent development of several high-plex 3D tissue imaging methods that provide new insight into cell states and interactions in the preserved environment of human specimens. I will also discuss how sophisticated data of this type can be used to advance simpler methods that represent a practical approache to the development of a new generation of multiplexed histopathological test for use in clinical trials and patient care. Such tests promise to improve outcomes and reduce the burden of therapy. Realizing these research and diagnostic possibilities requires the development of new instruments, reagents, and machine-learning algorithms. I will describe progress in these areas with reference to the characterization of immune landscapes in primary melanoma and predicting tumour progression in colorectal cancer.

Biosketch
Peter Sorger is the Otto Krayer Professor of Systems Biology at Harvard Medical School and Head of the Harvard Program in Therapeutic Sciences. His research focuses on single cell measurement and modeling of oncogenic networks in cancer and inflammatory diseases, particularly the interplay between tumor-intrinsic mechanisms of invasion and metastasis and countervailing immune surveillance. This is performed in human cohorts and mouse models to elucidate molecular programs controlling cancer progression and response to therapeutic drugs applied individually and in combination. His group is currently developing experimental and computational methods for high-plex single-cell analysis of human tumors and tissues in 2D and 3D. In a research setting, 50-100 plex imaging can be performed on conventional FFPE histological specimens at sufficient resolution to visualize individual drug targets and signaling complexes (PD1-PDL1 for example) across enough markers to deeply phenotype the constituents of the tissue microenvironment, including all major immune subtypes. In a translational setting, efficient lower-plex methods integrated with hematoxylin and eosin-based histology and machine learning/AI modeling enables creation of a new generation of image-based molecular diagnostics. The Sorger lab aims to develop these into companion biomarkers and prognostic tests able to guide clinical trials and more fully realize the promise of precision medicine.