Quantification of the Immunocellular Content in the Tumor Microenvironment

The emergence and success of immuno-oncology drugs in the treatment of several cancer types has transformed clinical practice. However, many patients do not respond to these drugs, compelling researchers and clinicians to broaden their search for biomarkers that can better predict therapy response. Historically, the identification of single, tumor-specific alterations has successfully served to determine the likelihood of beneficial response to targeted, precision oncology therapies. In contrast, response to immunotherapies, such as immune checkpoint modulators (ICMs), are largely dependent on both the tumor’s immunophenotype and its mutational profile, rendering the ability to analyze both tumor- and immune-related analytes within the tumor microenvironment (TME), a primary focus for oncology researchers today. Recent studies of current clinical biomarkers, such as tumor mutational burden (TMB), PD-L1 expression, and microsatellite instability (MSI) status have demonstrated suboptimal performance in separating responders from non-responders, exemplifying the need for additional biomarkers with improved predictive power.

Despite our understanding of the critical role that immune cells have to play in modern cancer treatment, traditional methods still lack the ability to accurately profile the presence of these cells within the TME of tumors. The gold-standard approach, immunohistochemistry (IHC), is burdened by its limited throughput, the difficulty associated with profiling multiple analytes simultaneously, and its laborious analytical process. Alternatively, flow cytometry requires a large amount of starting material and is typically incompatible with formalin-fixed paraffin embedded (FFPE) samples – the most commonly used technique for storing and preserving clinical tumor samples. For these reasons, Personalis has developed InfiltrateID, a sophisticated analytical module that quantitates the presence of eight immune cell populations in a tumor sample. This module leverages the augmented gene expression data derived from the NeXT Transcriptome™️ and is one of many analytical outputs of ImmunoID NeXT™, Personalis’ flagship immunogenomics platform, facilitating the simultaneous characterization of both the tumor and the immune  microenvironment from a single tumor specimen.