Tumors are formed by aggregates of cells of various origins including malignant, stromal and immune cells. The number of therapies targeting the microenvironment is increasing as the tumor microenvironment is more and more recognized as playing an essential role in tumor control. In the era of precision medicine, it is essential to precisely estimate the composition, organization and functionality of the individual patient tumor microenvironment and to find ways to therapeutically modulate it. To quantify the cell populations present in the tumor microenvironment, many tools are now available and the most recent approaches will be reviewed herein. We provide an overview of experimental and computational methodologies used to quantify tumor-associated cellular populations, including immunohistochemistry, flow and mass cytometry, bulk and single-cell transcriptomic approaches. We illustrate their respective contribution to characterize the microenvironment. We also discuss how these methods allow to guide therapeutic choices, in relation to the predictive value of some characteristics of the microenvironment.
Catalyzed reporter deposition, a novel method of signal amplification. II. Application to membrane immunoassays
Increased production of immature myeloid cells in cancer patients: a mechanism of immunosuppression in cancer
Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles
Deconvolution of blood microarray data identifies cellular activation patterns in systemic lupus erythematosus.
Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry
Optimal deconvolution of transcriptional profiling data using quadratic programming with application to complex clinical blood samples.
Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction
Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis
Orchestration and Prognostic Significance of Immune Checkpoints in the Microenvironment of Primary and Metastatic Renal Cell Cancer
Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints
Integrative Analyses of Colorectal Cancer Show Immunoscore Is a Stronger Predictor of Patient Survival Than Microsatellite Instability
Predictive Immunohistochemical Markers Related to Drug Selection for Patients Treated with Sunitinib or Sorafenib for Metastatic Renal Cell Cancer
Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression
Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade
Tumor-Infiltrating and Peripheral Blood T-cell Immunophenotypes Predict Early Relapse in Localized Clear Cell Renal Cell Carcinoma
PD-L1 Expression and CD8+ T-cell Infiltrate are Associated with Clinical Progression in Patients with Node-positive Prostate Cancer
Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
Prognostic impact of immune gene expression signature and tumor infiltrating immune cells in localized clear cell renal cell carcinoma
Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology
The Role of the Lymphocyte Functional Crosstalk and Regulation in the Context of Checkpoint Inhibitor Treatment-Review
Identification of Key Genes of Prognostic Value in Clear Cell Renal Cell Carcinoma Microenvironment and a Risk Score Prognostic Model.
The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression.
Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods.
Tumor Microenvironment and the Role of Artificial Intelligence in Breast Cancer Detection and Prognosis.
Identification of a novel autophagy signature for predicting survival in patients with lung adenocarcinoma.
A variety of different high-throughput technologies can be used to identify the complete catalog of changes that characterize the molecular profile of cohorts of tumor samples. Discover the latest insights gained from cancer 'omics' in this feed.