scholarly journals Increased Tumor Immune Microenvironment CD3+ and CD20+ Lymphocytes Predict a Better Prognosis in Oral Tongue Squamous Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Raísa Sales de Sá ◽  
Marisol Miranda Galvis ◽  
Bruno Augusto Linhares Almeida Mariz ◽  
Amanda Almeida Leite ◽  
Luciana Schultz ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Dendritic Cells ◽  
B Cells ◽  
Oral Tongue ◽  
Immune Microenvironment ◽  
Independent Prognostic Marker ◽  
Tumor Immune Microenvironment ◽  
Cell Subpopulations

Background: Oral tongue squamous cell carcinoma (OTSCC) causes over 350,000 cases annually and particularly impacts populations in developing countries. Smoking and alcohol consumption are major risk factors. Determining the role of the tumor immune microenvironment (TIME) in OTSCC outcomes can elucidate immune mechanisms behind disease progression, and can potentially identify prognostic biomarkers.Methods: We performed a retrospective study of 48 OTSCC surgical specimens from patients with tobacco and alcohol exposures. A panel of immunoregulatory cell subpopulations including T (CD3, CD4, CD8) and B (CD20) lymphocytes, dendritic cells (CD1a, CD83), macrophages (CD68), and immune checkpoint molecules programmed cell death protein 1 (PD-1) and ligand 1 (PD-L1) were analyzed using immunohistochemistry. The levels of immune effector cell subpopulations and markers were analyzed in relation to overall survival.Results: Pathological characteristics of the tumor microenvironment included inflammatory infiltrates (83.3%), desmoplasia (41.6%), and perineural invasion (50.0%). The TIME contained high levels of T cells (CD3+, CD4+, and CD8+) and B cells (CD20+), as well as immature (CD1a) and mature (CD83) dendritic cells, PD-1, and PD-L1. Higher numbers of TIME infiltrating CD3+ T cells and CD20+ B cells were predictive of better survival, while higher levels of CD83+ mature dendritic cells predicted better survival. CD3+ T cells were identified as an independent prognostic marker for OTSCC. Lastly, CD3+ T cells were strongly correlated with the number of CD8+ cells and PD-L1 expression.Conclusion: Our findings provide evidence that the TIME profile of OTSSC impacted prognosis. The high expression of CD3+ T cells and B cells are predictive of better overall survival and indicative of an immunologically active, inflammatory TIME in patients with better survival. The number of CD3+ T cells was an independent prognostic marker.

scholarly journals Characterization of the Tumor Immune Microenvironment in Lung Squamous Cell Carcinoma Using Imaging Mass Cytometry

2021 ◽  
Vol 11 ◽  
Author(s):  
Ran Li ◽  
Ying Lin ◽  
Yu Wang ◽  
Shaoyuan Wang ◽  
Yang Yang ◽  
...  
Keyword(s):  
Immune Response ◽  
Squamous Cell Carcinoma ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Lung Squamous Cell Carcinoma ◽  
Mass Cytometry ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Tumor Region ◽  
Proinflammatory Role

BackgroundLung squamous cell carcinoma (LUSC) is a major subtype of non-small cell lung cancer. The tumor immune microenvironment (TIME) affects the anti-tumor immune response and the patient’s prognosis, although the TIME in LUSC patients is incompletely understood.MethodsWe retrospectively collected surgical specimens from patients with previously untreated primary LUSC. Histopathological examination was used to identify tumor regions and adjacent regions, and imaging mass cytometry was used to characterize the immune cells in those regions. The results were compared between regions and between patients.ResultsWe identified heterogeneity in the TIME on comparing different patients with LUSC, although the tumor region and adjacent region both exhibited an immune response to the tumor. The TIME typically included a large number of infiltrating and activated T-cells, especially CD8+ T-cells, which closely interacted with the tumor cells in the tumor region. There was limited infiltration of B-cells, NK cells, and NKT cells, while the major immune suppressor cells were CD33+ myeloid-derived cells. We also identified a novel population of CD3−CD4+ cells with high expression of Foxp3 and TNFα, which might modulate the tumor microenvironment and play a proinflammatory role in the TIME.ConclusionsThe TIME of LUSC appears to be immunogenic and heterogenous, with predominant infiltration of activated CD8+ T-cells. The interactions between the tumor cells and T-cells facilitate the anti-tumor activity. A novel subpopulation of CD3−CD4+ cells with high TNFα and Foxp3 expression may modulate the tumor microenvironment and play a proinflammatory role.

scholarly journals Statistical framework for studying the spatial architecture of the tumor immune microenvironment

2021 ◽  
Author(s):  
Christopher Wilson ◽  
Ram Thapa ◽  
Jordan Creed ◽  
Jonathan Nguyen ◽  
Carlos Moran Segura ◽  
...  
Keyword(s):  
Overall Survival ◽  
T Cells ◽  
Immune Cells ◽  
Spatial Clustering ◽  
Cytotoxic T Cells ◽  
Tumor Infiltrating Lymphocytes ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Infiltrating Lymphocytes ◽  
Spatial Architecture

AbstractNew technologies, such as multiplex immunofluorescence microscopy (mIF), are being developed and used for the assessment and visualization of the tumor immune microenvironment (TIME). These assays produce not only an estimate of the abundance of immune cells in the TIME, but also their spatial locations; however, there are currently few approaches to analyze the spatial context of the TIME. Thus, we have developed a framework for the spatial analysis of the TIME using Ripley’s K, coupled with a permutation-based framework to estimate and measure the departure from complete spatial randomness (CSR) as a measure of the interactions between immune cells. This approach was then applied to ovarian cancer using mIF collected on intra-tumoral regions of interest (ROIs) and tissue microarrays (TMAs) from 158 high-grade serous ovarian carcinoma patients in the African American Cancer Epidemiology Study (AACES) (94 subjects on TMAs resulting in 259 tissue cores; 91 subjects with 254 ROIs). Cox proportional hazard models were constructed to determine the association of abundance and spatial clustering of tumor-infiltrating lymphocytes, cytotoxic T-cells, and regulatory T-cells, and overall survival. We found that EOC patients with high abundance and low spatial clustering of tumor-infiltrating lymphocytes and cytotoxic T-cells in their tumors had the best overall survival. In contrast, patients with low levels of regulatory T-cells but with a high level of spatial clustering (compare to those with a low level of spatial clustering) had better survival. These findings underscore the prognostic importance of evaluating not only immune cell abundance but also the spatial contexture of the immune cells in the TIME. In conclusion, the application of this spatial analysis framework to the study of the TIME could lead to the identification of immune content and spatial architecture that could aid in the determination of patients that are likely to respond to immunotherapies.

scholarly journals Screening of tumor microenvironment-related prognostic genes in breast cancer by data mining

2020 ◽  
Author(s):  
Yunhui LI ◽  
Na REN
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
B Cells ◽  
Memory T Cells ◽  
Immune Therapy ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Immune Score

Abstract Background Accumulating evidence has demonstrated that the components of tumor immune microenvironment (TME) play important roles in breast cancer (BC) initiation, progression and prognosis. Materials and methods We downloaded the TCGA, GSE12276, GSE58812 and GSE42568 datasets. We calculated the immune scores and tumor immune infiltrating cells (TIICs) of TCGA-BRCA and GEO datasets using ESTIMATE and CIBERSORT algorithm, respectively. Then, the overlapping immune-related differentially expressed genes (DEGs) were screened using R ‘limma ’ package between TCGA and GSE12276 datasets. The GO and KEGG enrichment analysis were used to predict the function and signaling pathways of common DEGs. Finally, we extracted a series of tumor immune microenvironment-related genes, and explore the relationship between these genes and clinical outcomes in TCGA, GSE58812 and GSE42568 datasets. Results Based on the ESTIMATE algorithm, the immune scores were significantly associated with cancer types, as well as overall survival in BC patients. The fractions of some TIICs, such asnaïve B cells, memory B cells, CD8 + T cells, resting CD4 + memory T cells, activated CD4 + memory T cells, resting NK cells, monocytes, macrophage M0, M1, M2, resting DCs, activated DCs and resting mast cells, were significantly different between low and high immune score groups (all P <0.05). The DEGs between low and high immune score groups were mainly involved in immune-related biological processes, including adaptive immune response, innate response and inflammatory response. Finally, we found that ACSL5, GIMAP2, HLA-DRA and CLEC10A were significantly associated with prognosis among TCGA, GASE58812 and GSE42568 datasets (all P <0.05). Conclusion These findings provide a more comprehensive understanding of immune cells and immune-related genes within TME as well as prognosis-related genes in BC. Future studies need to perform in vivo and in vitro experiments to clarify the mechanisms of these genes in TME and provide a comprehensive idea to immune therapy.

scholarly journals Transcriptomic and Immunophenotypic Characterization of Tumor Immune Microenvironment in Squamous Cell Carcinoma of the Oral Tongue

2020 ◽  
Author(s):  
Kyriakos Chatzopoulos ◽  
Sotiris Sotiriou ◽  
Andrea R. Collins ◽  
Panagiotis Kartsidis ◽  
Alessandra C. Schmitt ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Oral Tongue ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment

Utilizing quantitative multiplex immunofluorescence to characterize paracrine interactions within the tumor-immune landscape of metastatic melanoma.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15184-e15184
Author(s):  
Rachel L. Maus ◽  
Alexey Leontovich ◽  
Raymond Moore ◽  
Wendy Kay Nevala ◽  
Thomas J. Flotte ◽  
...  
Keyword(s):  
T Cells ◽  
B Cells ◽  
Metastatic Melanoma ◽  
Immune Reactivity ◽  
Cellular Composition ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Treatment Naïve ◽  
Clinical Responses ◽  
Tumor Infiltrate

e15184 Background: Clinical responses to anti-PD1 immunotherapy in patients with metastatic melanoma (MM) remain challenging to predict. This clinical heterogeneity is also reflected in the tumor-immune microenvironment among patients and within a single tumor lesion. With the emergence of multiplex imaging platforms, defining complex phenotypes at single cell resolution has become possible. Here, we sought to objectively quantify paracrine tumor-immune interactions contributing to the variable clinical responses observed in patients receiving anti-PD1 therapy. Methods: Excisional lymph node (LN) biopsies were obtained from treatment-naïve patients with MM who underwent subsequent anti-PD1 therapy. A single 5µm section of LN tissue was used to assess a 42 analyte panel by multiplex immunofluorescence. From 30 LN samples, 418 fields of view (FOVs) were selected resulting in 14,360 high-resolution images of 4 anatomical subregions: tumor core, tumor-immune interface, tumor infiltrate and adjacent immune stroma. Following image processing, we developed an adaptive classification for tumor-centric cellular neighborhoods (TCCN) to identify and quantify critical paracrine interactions within the tumor-immune microenvironment. Results: Stratification based on responsiveness to anti-PD1 therapy resulted in 4 complete responders (CR) and 12 non-responders (NR) at 12-week follow-up. From 126 FOVs, we defined the cellular composition of 197,865 TCCN across patients based on clinical response and LN subregions. Overall, the percentage of TCCN devoid of any T cells, B cells or macrophages was significantly higher in NR compared to CR irrespective of subregion. However, other markers differentiated TCCN based on subregion. Specifically in CR, tumor core regions were enriched for CD8 T cells, while enrichment for B cells and endothelial cells was demonstrated at the tumor-immune interface. Strikingly, tumor infiltrate regions demonstrate robust immune reactivity with enrichment for M1 polarized macrophages, NK cells and B cells in CR compared to NR. Complete data from the 30 patient cohort across 418 FOVs will be presented. Conclusions: Taken together, this data suggests cellular composition of TCCN across subregions of the LN is dynamic within a single metastatic site. In this small cohort, we introduce a formalized stratification to quantify and classify critical paracrine interactions within the immune-tumor microenvironment with the potential to inform clinical responsiveness to therapy.

scholarly journals Relapsed multiple myeloma demonstrates distinct patterns of immune microenvironment and malignant cell-mediated immunosuppression

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Alissa Visram ◽  
Surendra Dasari ◽  
Emilie Anderson ◽  
Shaji Kumar ◽  
Taxiarchis V. Kourelis
Keyword(s):  
Multiple Myeloma ◽  
T Cells ◽  
Plasma Cells ◽  
Malignant Cell ◽  
Immune Microenvironment ◽  
Cytokine Analysis ◽  
Tumor Immune Microenvironment ◽  
Early Memory ◽  
E2f Transcription Factors ◽  
Cluster 2

AbstractImmunotherapy has shown efficacy in relapsed multiple myeloma (MM). However, these therapies may depend on a functional tumor immune microenvironment (iTME) for their efficacy. Characterizing the evolution of the iTME over the disease course is necessary to optimize the timing of immunotherapies. We performed mass cytometry, cytokine analysis, and RNA sequencing on bone marrow samples from 39 (13 newly diagnosed [NDMM], 11 relapsed pre-daratumumab exposure [RMM], and 13 triple-refractory [TRMM]) MM patients. Three distinct cellular iTME clusters were identified; cluster 1 comprised mainly of NDMM and RMM patients; and clusters 2 and 3 comprised primarily of TRMM patients. We showed that naive T cells were decreased in clusters 2 and 3, cluster 2 was characterized by increased senescent T cells, and cluster 3 by decreased early memory T cells. Plasma cells in clusters 2 and 3 upregulated E2F transcription factors and MYC proliferation pathways, and downregulated interferon, TGF-beta, interleuking-6, and TNF-αlpha signaling pathways compared to cluster 1. This study suggests that the MM iTME becomes increasingly dysfunctional with therapy whereas the MM clone may be less dependent on inflammation-mediated growth pathways and less sensitive to IFN-mediated immunosurveillance. Our findings may explain the decreased sensitivity of TRMM patients to novel immunotherapies.

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