Abstract
The immune microenvironment in lung squamous cell carcinoma (LUSC) is not well understood, with interactions between the host immune system and the tumor, as well as the molecular pathogenesis of LUSC, awaiting better characterization. To date, no molecularly targeted agents have been developed for LUSC treatment. Identification of predictive and prognostic biomarkers for LUSC could help optimize therapy decisions. We sequenced whole exomes and RNA from 101 tumors and matched noncancer control Korean samples. We used the information to predict subtype-specific interactions within the LUSC microenvironment and to connect genomic alterations with immune signatures. Hierarchical clustering based on gene expression and mutational profiling revealed subtypes that were either immune defective or immune competent. We analyzed infiltrating stromal and immune cells to further characterize the tumor microenvironment. Elevated expression of macrophage 2 signature genes in the immune competent subtype confirmed that tumor-associated macrophages (TAM) linked inflammation and mutation-driven cancer. A negative correlation was evident between the immune score and the amount of somatic copy-number variation (SCNV) of immune genes (r = -0.58). The SCNVs showed a potential detrimental effect on immunity in the immune-deficient subtype. Knowledge of the genomic alterations in the tumor microenvironment could be used to guide design of immunotherapy options that are appropriate for patients with certain cancer subtypes. Cancer Immunol Res; 6(7); 848-59. ©2018 AACR.
Highlights
Lung cancer is the second leading cause of death in Korea
Identification of lung squamous cell carcinoma (LUSC) subtypes In this study, 101 LUSC and matched noncancer control samples were used to discover significant differential gene expression, and principal component analysis (PCA) on entire samples was performed to identify distinctive clusters based on gene variability between LUSC and noncancer control samples
PCA with the top 1,000 most variable genes and unsupervised hierarchical clustering with the k-means algorithm were applied to RNA-seq data and distinguished noncancer control from tumor samples
Summary
Lung cancer is the second leading cause of death in Korea. The most common type of primary lung cancer, lung adenocarcinoma, has been characterized at the molecular level [1, 2]. Lung squamous cell carcinoma, which accounts for 30% of all lung cancers [3], is not well characterized due to poor understanding of the cancer's genomic evolution [4] and the antitumor activity of immune cells [5, 6]. Genomic alterations in the tumor characterize various stages of cancer progression. On the other hand, are governed by tumor stroma, including basement membrane, extracellular matrix, vasculature, and cells of the. Note: Supplementary data for this article are available at Cancer Immunology Research Online (http://cancerimmunolres.aacrjournals.org/).
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