Multi-Omics Profiling of the Tumor Microenvironment: Paving the Way to Precision Immuno-Oncology

Abstract

The tumor microenvironment (TME) is a multifaceted ecosystem characterized by profound cellular heterogeneity, dynamicity, and complex intercellular cross-talk. The striking responses obtained with immune checkpoint blockers, i.e., antibodies targeting immune-cell regulators to boost antitumor immunity, have demonstrated the enormous potential of anticancer treatments that target TME components other than tumor cells. However, as checkpoint blockade is currently beneficial only to a limited fraction of patients, there is an urgent need to understand the mechanisms orchestrating the immune response in the TME to guide the rational design of more effective anticancer therapies. In this Mini Review, we give an overview of the methodologies that allow studying the heterogeneity of the TME from multi-omics data generated from bulk samples, single cells, or images of tumor-tissue slides. These include approaches for the characterization of the different cell phenotypes and for the reconstruction of their spatial organization and inter-cellular cross-talk. We discuss how this broader vision of the cellular heterogeneity and plasticity of tumors, which is emerging thanks to these methodologies, offers the opportunity to rationally design precision immuno-oncology treatments. These developments are fundamental to overcome the current limitations of targeted agents and checkpoint blockers and to bring long-term clinical benefits to a larger fraction of cancer patients.

Keywords: bioinformatics; immuno-oncology; multi-omics profiling; next-generation sequencing; systems biology; systems immunology; tumor microenvironment; tumor-infiltrating immune cells.

Figure 1

Overview of the main approaches for multi-omics profiling of the tumor microenvironment (TME). Omics datasets can be generated from bulk tumor samples; this approach is the most standardized and widely used and provides a high-throughput representation of the molecular features (e.g., genome, transcriptome, proteome) of the TME as a whole. Unlike the averaged representation provided by bulk approaches, single-cell technologies allow generating omics profiles of each individual cell; however, their costs and technical complexity currently limit the throughput in terms of number of features and total cells that can be assayed. Emerging imaging techniques can generate omics datasets from tumor-tissue slides that retain the cell spatial resolution; they have cellular or subcellular resolution but their throughput is significantly lower compared to the other two approaches and the resulting images only represent a restricted 2D snapshot of the tumor.

Figure 2

Representation of some of the facets of the tumor microenvironment (TME). (A) The expression of mutated genes can generate tumor-specific neoantigens, i.e., peptides bound to the tumor cell HLAs that can be recognized by T cells and elicit an immune response. (B) The quantification of the different cell types of the TME, which can have pro- or anti-tumorigenic roles, can provide prognostic, and predictive markers for immunotherapy. (C) The immense diversity of lymphocyte receptors, which can be different from lymphocyte to lymphocyte, allows the immune system coping with a wealth of unpredictable antigens and varies greatly depending on spontaneous or therapy-induced anticancer immune responses. (D) During tumor progression, cancer cells accumulate somatic mutations that increase intra-tumoral heterogeneity and can change cell fitness and response to drugs. (E) The TME is composed of various cell subtypes (e.g., CD4+ and CD8+ T cell), which are in turn characterized by different functional orientations (e.g., naïve, effector, memory CD8+ T cell) and states (e.g., activated, anergic, exhausted CD8+ T cell). (F) The spatial organization of cells, such as cell neighbors (e.g., proximity of tumor and immune cells) or cellular patterns (i.e., tissue motifs, such as stem-cell niches), reflects biological processes at the tissue level. (G) Cells constantly exchange signals with surrounding cells by secreting molecules (e.g., cytokines, chemokines, growth factors) or by direct ligand-receptor binding on the cell surfaces (e.g., immune checkpoints). (H) When ligands bind to cell receptors, the cell responds by processing this signal through a complex signal transduction network that transmits information to the nucleus, where transcription factors regulate the transcriptional response of the cell. (I) Most of cancer therapies, such as immunotherapy with immune checkpoint blockers or targeted therapy, act on molecules responsible for inter- and intra-cellular communication that are deregulated in cancer, trying to restore the normal behavior of the cells.