Peter P. Lee - Tumor Microenvironment

Adoptive Cellular Therapy

C-C motif chemokine Receptor

Cancer Immune Responsiveness

Checkpoint Inhibitor Therapy

Damage Associated Molecular Patterns

Food and Drug Administration

High-mobility group box protein 1

Immunogenic Cell Death

Immunologic Constant of Rejection

Interferon

Immune Oncology

Major Histocompatibility Complex

Mechanism Of Action

Programmed Cell Death-1

Programmed death ligand-1

The Cancer Genome Atlas

Tumor-Infiltrating Lymphocytes

Tumor Inflammation Signature

Tumor Microenvironment

The spatial distribution, density, and functional orientation of intratumoral immune infiltrates define the continuum of cancer immune surveillance. Variables clustered in a four-dimensional space and time contribute to cancer immune phenotypes: genetic background of the host, somatic evolution of cancer cells, environmental influences, and dynamic changes molded by spontaneous or treatment-induced host immune response. Unstable cancer genetics can activate almost infinite paths to promote survival during this evolutionary process. However, tumors have to confront a bottleneck determined by highly conserved mechanisms of innate and adaptive immune recognition. This interaction limits growth strategies to a binary choice: either adopt an orderly progression of essential genetic alterations that parallels the differentiation of stem cells during organ development or follow a stochastic hyper mutational path that stimulates multiple tissue regenerating properties by surrounding tissues like in a healing wound at the cost of creating a hyperactive environment in excess of chemo-attractive and inflammatory processes. This in turn is conducive to intratumoral immune infiltration and activation. Increasing knowledge is refining this multidimensional and dynamic view of cancer evolution and its prognostic and therapeutic implications. Direct analysis of the tumor microenvironment (TME) can dissect the biology underlying cancer immune responsiveness (CIR) by looking for predictors of response, understanding mechanisms of action (MOA) of therapeutics, and documenting strategies adopted by cancer cells to escape immune control. These elements will be the focus of this book.

Our view of tumors has greatly expanded from simply a mass of homogeneous cancer cells to a complex ecosystem consisting of heterogeneous cancer cells, stromal cells, and immune cellscollectively termed the tumor microenvironment (TME). Accumulating evidence demonstrate that patient outcome is significantly impacted by the immune contexture of the tumor as a reflection of host immune surveillance. Beyond numbers, it is also becoming recognized that the spatial distribution and functional orientation of immune cells infiltrating tumors define the continuum of cancer immune surveillance, its natural history, and responsiveness to treatment [1]. We have long advocated the use of serially obtained tumor biopsies for a dynamic understanding of cancer immune responsiveness (CIR) with the goal of identifying predictors (from pre-treatment samples), documenting MOAs (on treatment samples), and understanding immune escape (post-treatment biopsies) [2, 3]. This approach led to the original observation that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition [4, 5] in the context of a melanoma differentiation antigen-based vaccine administered in combination with human recombinant interleukin-2. Ranking of gene expression data from pre-treatment samples identified approximately 30 genes predictive of clinical response (P < 0.001), most of them with immune function. This conclusion was subsequently corroborated by several studies that led to a basic understanding of the mechanisms of cancer rejection [614] with not only predictive, but also prognostic implications [1, 1517]. Indeed, cancer rejection [13] was recognized to be a facet of the broader and evolutionarily conserved phenomenon of immune-mediated tissue-specific destruction: a mechanism that we termed the Immunologic Constant of Rejection (