Wes And Milo Synergize To Profile Immune Cell Populations In The Tumor Microenvironment

Immunotherapy has opened the door to a new era in cancer treatment where dramatically successful and durable responses are being reported. Still, the population of patients who respond are a minority, and this highlights the need for a deeper understanding of the immune response to cancer. To that end, accumulating evidence suggests that the heterogeneous makeup of the tumor microenvironment (TME) is a major contributor to the discrepancies in response observed.

The TME is an integrated network of cancerous, noncancerous and immune cell types whose interactions drive tumor heterogeneity, metastatic spread and acquired drug resistance. In particular, the infiltration of leukocytes in the TME, including lymphocytes, macrophages and dendritic cells, among others, has been recognized as both an important prognostic factor and a major obstacle to cancer immunotherapy success2–4. Broadly speaking, infiltrating CD8+ T lymphocytes are associated with a proinflammatory TME signature and a better therapeutic response. Working out the cellular determinants behind CD8+ T cell recruitment is requisite to retaining that favorable therapeutic response. Then there’s the presence of inhibitory immune cell types and subsets, which, in general, work to suppress a tumor-specific immune response—an attractive target in multimodal treatment strategies to come.

Profiling the composition and function of immune cells that exist within the TME is poised to guide an improved response to immunotherapy and may uncover novel therapeutic targets and strategies. But the complexity and heterogeneity of immune cell signatures, combined with a finite sample, make the TME a particularly difficult area of investigation for which advanced tools are required to achieve deeper analyses. In this application note, we’ll show you how Wes™ and Milo™ partner to get you critical answers to 1) what type of immune cell populations are present in a sample and then 2) what percentage of cells in that sample make up a specific immune cell subtype. The workflow gives you a population-level and single-cell-level perspective on each sample analyzed, a much faster time to result than the traditional approach you may currently be using and saves on your sample, big-time.