Tumor Microenvironment and Immunotherapy Response in Head and Neck Cancer

The tumor microenvironment (TME) encompasses cellular and non-cellular components which play an important role in tumor evolution, invasion, and metastasis. A complicated interplay between tumor cells and adjacent TME cells, such as stromal cells, immune cells, inflammatory cells, and cytokines, leads to severe immunosuppression and the proliferation of cancer cells in several solid tumors. An immunosuppressive TME has a significant impact on treatment resistance and may guide response to immunotherapy. In head and neck cancer (HNC), immunotherapeutic drugs have been incorporated in everyday clinical practice. However, despite an exceptional rate of durable responses, only a low percentage of patients respond. In this review, we will focus on the complex interactions occurring in this dynamic system, the TME, which orchestrate key events that lead to tumor progression, immune escape, and resistance. Furthermore, we will summarize current clinical trials that depict the TME as a potential therapeutic target for improved patient selection.

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Advancement in Cancer Stem Cell Biology and Precision Medicine—Review Article Head and Neck Cancer Stem Cell Plasticity and the Tumor Microenvironment

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.660210 ◽

2022 ◽

Vol 9 ◽

Author(s):

Molly E. Heft Neal ◽

J. Chad Brenner ◽

Mark E. P. Prince ◽

Steven B. Chinn

Keyword(s):

Head And Neck Cancer ◽

Stem Cell ◽

Tumor Microenvironment ◽

Cancer Stem Cell ◽

Head And Neck ◽

Neck Cancer ◽

Treatment Resistance ◽

Cell Plasticity ◽

Stem Cell Plasticity ◽

Cell Niche

Head and Neck cancer survival has continued to remain around 50% despite treatment advances. It is thought that cancer stem cells play a key role in promoting tumor heterogeneity, treatment resistance, metastasis, and recurrence in solid malignancies including head and neck cancer. Initial studies identified cancer stem cell markers including CD44 and ALDH in head and neck malignancies and found that these cells show aggressive features in both in vitro and in vivo studies. Recent evidence has now revealed a key role of the tumor microenvironment in maintaining a cancer stem cell niche and promoting cancer stem cell plasticity. There is an increasing focus on identifying and targeting the crosstalk between cancer stem cells and surrounding cells within the tumor microenvironment (TME) as new therapeutic potential, however understanding how CSC maintain a stem-like state is critical to understanding how to therapeutically alter their function. Here we review the current evidence for cancer stem cell plasticity and discuss how interactions with the TME promote the cancer stem cell niche, increase tumor heterogeneity, and play a role in treatment resistance.

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Author response for "CD8+CD73+ T cells in the tumor microenvironment of head and neck cancer patients are linked to diminished T cell infiltration and activation in tumor tissue"

10.1002/eji.202048626/v2/response1 ◽

2020 ◽

Author(s):

Soumya Panigrahi ◽

Douglas A. Bazdar ◽

Marwah Albakri ◽

Brian Ferrari ◽

Christopher J. Antonelli ◽

...

Keyword(s):

T Cells ◽

Head And Neck Cancer ◽

T Cell ◽

Tumor Microenvironment ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Tumor Tissue ◽

Author Response ◽

T Cell Infiltration

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Review for "CD8+CD73+ T cells in the tumor microenvironment of head and neck cancer patients are linked to diminished T cell infiltration and activation in tumor tissue"

10.1002/eji.202048626/v1/review2 ◽

2020 ◽

Keyword(s):

T Cells ◽

Head And Neck Cancer ◽

T Cell ◽

Tumor Microenvironment ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Tumor Tissue ◽

Cell Infiltration ◽

T Cell Infiltration

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Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

10.1101/278887 ◽

2018 ◽

Author(s):

An-Shun Tai ◽

Chien-Hua Peng ◽

Shih-Chi Peng ◽

Wen-Ping Hsieh

Keyword(s):

Head And Neck Cancer ◽

Head And Neck ◽

Neck Cancer ◽

Copy Number ◽

Tumor Heterogeneity ◽

Tumor Evolution ◽

Depth Information ◽

Sequencing Data ◽

Single Nucleotide Variants ◽

Copy Number Aberrations

AbstractMultistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

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