The Krieg lab combines high-dimensional single-cell techniques with bioinformatics analysis to define new cellular biomarkers. Using our workflow, we recently described cellular biomarker signatures to predict the response of patients with melanoma to immunotherapy and patients with therapy-resistant lung cancer to novel combination immunotherapy. In addition, the Krieg lab recently expanded its effort into using multi-platform technologies, such as MALDI-IMS and imaging mass cytometry, to identify and characterize single-cells in tissues.

Single-cell omics and imaging technologies hold great promise for understanding the complex interactions between tumor and immune cells in the tumor microenvironment. I will present how these technologies can be applied to clinical samples to untangle tumor-immune cell interactions in both leukemia and solid tumors.

Biological functions arise from protein interactions, which are reflected in the natural variation of proteome configurations across individual cells. Emerging single-cell proteomics methods may decode this variation and empower inference of biological mechanisms with minimal assumptions. I will describe both established and emerging single-cell mass-spectrometry methods, and how these methods have allowed us to interpret protein covariation in different biological systems, including primary macrophages and melanoma cells.

Historically, cancer drugs are combined orthogonally to overcome resistance. “Independent Action” mathematically tests this approach. In the immuno-oncology (IO) era, efforts to rationally design combinations have led to a surge of trials proposing “synergy.” The failure of scientists to understand pharmacologic synergy may be contributing to increasing futility in moving cancer drugs from Phase 1 to registration. Clinical “synergy” is very rare in drug development, especially in IO combinations.       

The genomic revolution has demonstrated that targeted drugs, in order to be useful, must be given to patients whose tumors bear the cognate target. For instance, EGFR kinase inhibitors are active against cancers with EGFR kinase mutations, but inactive against cancers without the targeted alteration. Similarly, optimizing immunotherapy will require a precision approach, i.e., identification of malignancies that harbor an immune target modifiable by the specific immunotherapy given.

In this talk, we present a rapid 3D molecular imaging and computational suite for highly multiplexed single-molecule RNA-FISH-based spatial transcriptomic approaches. Building on our recent work in high-resolution oblique plane microscopy and model-driven data analysis, this approach provides 3D localization in large samples at speeds equal to or greater than existing microscopy approaches. We provide example results for highly multiplexed RNA-FISH from cells to human tissue slices.

Given the functional importance of the physical arrangement of diverse cell types and cell states in the CNS, single-cell and spatially resolved –omics methods could provide fundamental insights into the molecular and cellular pathologies in neurodegenerative diseases. We have assembled an accessible toolkit of instrumentation, molecular profiling, and computational technologies for integrative multimodal atlasing of CNS tissues at scale. Using this toolkit, we are generating datasets enabling analysis of the links between genotype, gene regulation, pathology, and clinical presentation.

Fibroblasts are non-hematopoietic structural cells that regulate tissue architecture, support homeostasis of tissue-resident cells, and play pivotal roles in biological processes such as fibrosis, cancer, autoimmunity, and wound-healing. We apply multi-modal single cell and spatial methods to identify and characterize universal fibroblasts that serve as a reservoir and yield both specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts across disease. Our integrative analyses of fibroblasts represent an effort into implementing sophisticated single-cell methods towards the discovery of novel fundamental biology which will yield clinical dividends.

Tissue functions are highly cell non-autonomous. While single-cell analysis has begun to elucidate the cellular components that participate in tissue function and dysfunction; interactions – and their spatial variation across tissue structures – remain challenging to explore. Here, we’ll describe advances in situ and single cell transcriptomic sequencing tools which aim to capture both the spatial context of cells as well as their dynamics within tissues. We will describe efforts to apply these tools to measure, model and manipulate the rules of tissue organization in diverse contexts. More broadly, we’ll discuss the promise and challenges of spatial transcriptomics for tissue genomics.

Multiplexed immune cell profiling of the tumor microenvironment (TME) has improved our understanding of cancer immunology. We have used imaging mass cytometry (IMC) to characterize the tumor and immune cell architecture of aggressive lymphoma. We integrate tumor mutational profiling, clinical outcomes, and multiplexed immuno-phenotyping of the TME into a spatial analysis of lymphoma at the single cell level and identify candidate biomarkers for treatment response.

Cellular “maps” shed light on the spatial regulation mechanisms of many disorders. The next challenge in spatial biology is to link the cellular function to the cell phenotypes in their environments. Image-based multiparameter molecular profiling has the potential to decode high-dimensional dynamics of signaling and metabolism at the subcellular and molecular level in complex tissues and organs. In this talk, I will introduce multiplex imaging modalities (genomics, proteomics, and metabolomics) to decipher the spatial and temporal decision-making of single-cells at macromolecular resolution in engineered organoids and human tissues for systems immuno-engineering, subcellular precision oncology, and personalized regenerative medicine applications.