Abstract

Non-small cell lung carcinoma (NSCLC) is a complex cancer biome composed of malignant cells embedded in a sophisticated tumor microenvironment (TME) combined with different initiating cell types, including immune cells and cancer-associated fibroblasts (CAFs), and extracellular matrix (ECM) proteins. However, little is known about these tumors’ immune-matricellular relationship as functional and mechanical barriers. This study investigated 120 patients with NSCLC to describe the immune-matricellular phenotypes of their TME and their relationship with malignant cells. Immunohistochemistry (IHC) was performed to characterize immune checkpoints (PD-L1, LAG-3, CTLA-4+, VISTA 1), T cells (CD3+), cytotoxic T cells (CD8+, Granzyme B), macrophages (CD68+), regulatory T cells (FOXP3+, CD4+), natural killer cells (CD57+), and B lymphocytes (CD20+), whereas CAFs and collagen types I, III, and V were characterized by immunofluorescence (IF). We observed two distinct functional immune-cellular barriers—the first of which showed proximity between malignant cells and cytotoxic T cells, and the second of which showed distant proximity between non-cohesive nests of malignant cells and regulatory T cells. We also identified three tumor-associated matricellular barriers: the first, with a localized increase in CAFs and a low deposition of Col V, the second with increased CAFs, Col III and Col I fibers, and the third with a high amount of Col fibers and CAFs bundled and aligned perpendicularly to the tumor border. The Cox regression analysis was designed in two steps. First, we investigated the relationship between the immune-matricellular components and tumor pathological stage (I, II, and IIIA), and better survival rates were seen in patients whose tumors expressed collagen type III > 24.89 fibers/mm². Then, we included patients who had progressed to pathological stage IV and found an association between poor survival and tumor VISTA 1 expression > 52.86 cells/mm² and CD3+ ≤ 278.5 cells/mm². We thus concluded that differential patterns in the distribution of immune-matricellular phenotypes in the TME of NSCLC patients could be used in translational studies to predict new treatment strategies and improve patient outcome. These data raise the possibility that proteins with mechanical barrier function in NSCLC may be used by cancer cells to protect them from immune cell infiltration and immune-mediated destruction, which can otherwise be targeted effectively with immunotherapy or collagen therapy.

Highlights

  • The progression and prognosis of non-small cell lung carcinomas (NSCLC) remain a problem for both oncologists and patients

  • In order to address these gaps in the literature, we evaluated the relationship between those known markers of the immunological journey in NSCLC and matricellular proteins, most of them involved in functional and mechanical molecular barriers and cell block motility that support NSCLC invasion and metastases in localized surgically resected primary tumor

  • The tumors were histologically classified as an adenocarcinoma in 73 patients (60.8%), a squamous cell carcinoma in 40 patients (33.3%), and a large cell carcinoma in 7 patients (5.8%)

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Summary

Introduction

The progression and prognosis of non-small cell lung carcinomas (NSCLC) remain a problem for both oncologists and patients. NSCLC is a complex cancer biome composed of malignant cells embedded in a sophisticated tumor microenvironment (TME) with different and combined initiating cell types, including CAFs, and extracellular matrix (ECM) proteins. The TME is regulated by continuous epithelial-to-mesenchymalECM interactions, which are recognized as key actors in the theatrical scenario for progression of primary lung carcinoma [3,4,5,6]. In the ECM, a variety of collagen proteins provide the framework for parenchymal and stroma alignment, working as a mechanical barrier that regulates cancer cell growth and motility [7], whereas immune checkpoints, macrophages, T cells, and natural killer (NK) cells represent the functional immune barrier

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