scholarly journals The PPARγ Agonist Rosiglitazone Suppresses Syngeneic Mouse SCC (Squamous Cell Carcinoma) Tumor Growth through an Immune-Mediated Mechanism

Molecules ◽  
2019 ◽  
Vol 24 (11) ◽  
pp. 2192 ◽  
Author(s):  
Raymond L. Konger ◽  
Ethel Derr-Yellin ◽  
Nurmukambed Ermatov ◽  
Lu Ren ◽  
Ravi P. Sahu

Recent evidence suggests that PPARγ agonists may promote anti-tumor immunity. We show that immunogenic PDV cutaneous squamous cell carcinoma (CSCC) tumors are rejected when injected intradermally at a low cell number (1 × 106) into immune competent syngeneic hosts, but not immune deficient mice. At higher cell numbers (5 × 106 PDV cells), progressively growing tumors were established in 14 of 15 vehicle treated mice while treatment of mice with the PPARγ agonist rosiglitazone resulted in increased tumor rejection (5 of 14 tumors), a significant decrease in PDV tumor size, and a significant decrease in tumor cell Ki67 labeling. Rosiglitazone treatment had no effect on tumor rejection, tumor volume or PDV tumor cell proliferation in immune deficient NOD.CB17-PrkdcSCID/J mice. Rosiglitazone treatment also promoted an increase in tumor infiltrating CD3+ T-cells at both early and late time points. In contrast, rosiglitazone treatment had no significant effect on myeloid cells expressing either CD11b or Gr-1 but suppressed a late accumulation of myeloid cells expressing both CD11b and Gr-1, suggesting a potential role for CD11b+Gr-1+ myeloid cells in the late anti-tumor immune response. Overall, our data provides evidence that the PPARγ agonist rosiglitazone promotes immune-mediated anti-neoplastic activity against tumors derived from this immunogenic CSCC cell line.

2021 ◽  
pp. 028418512198897
Author(s):  
Alexey Surov ◽  
Maciej Pech ◽  
Alexander Eckert ◽  
Christoph Arens ◽  
Oliver Grosser ◽  
...  

Background Head and neck squamous cell carcinoma (HNSCC) is a common cancer. Positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) is a widely used imaging modality in HNSCC. Purpose To provide evident data about associations between 18F-FDG PET and histopathology in HNSCC. Material and Methods The MEDLINE database was screened for associations between maximum standard uptake values (SUVmax) derived from 18F-FDG PET and histopathological features in HNSCC up to May 2020. Only papers containing correlation coefficients between SUVmax and histopathology were acquired. Overall, 23 publications were collected. Results The following correlations were calculated: KI 67: 12 studies (345 patients), pooled correlation coefficient (PCC): 0.23 (95% confidence interval [CI] 0.06–0.40); hypoxia-inducible factor-1α: eight studies (240 patients), PCC: 0.24 (95% CI 0.06–0.42); microvessel density: three studies (64 patients), PCC: 0.33 (95% CI 0.02–0.65); vascular endothelial growth factor: two studies (59 cases), PCC: 0.27 (95% CI 0.02–0.51); tumor suppressor protein p53: four studies (159 patients), PCC: 0.05 (95% CI –0.41 to 0.51); epidermal growth factor receptor: two studies (124 patients), PCC: 0.21 (95% CI 0.05–0.37); tumor cell count: three studies (67 patients), PCC: 0.18 (95% CI –0.06 to 0.42); tumor cell apoptosis: two studies (40 patients), PCC: 0.07 (95% CI = –0.85 to 0.99); B-cell lymphoma-2 protein: two studies (118 patients); PCC: 0.04 (95% CI –0.65 to 0.74); glucose-transporter 1: 10 studies (317 patients), PCC: 0.20 (95% CI 0.10–0.30). Conclusion SUVmax derived from 18F-FDG PET cannot reflect relevant histopathological features in HNSCC.


2021 ◽  
Vol 12 ◽  
Author(s):  
Kanako Yoshimura ◽  
Takahiro Tsujikawa ◽  
Junichi Mitsuda ◽  
Hiroshi Ogi ◽  
Sumiyo Saburi ◽  
...  

BackgroundFunctional interactions between immune cells and neoplastic cells in the tumor immune microenvironment have been actively pursued for both biomarker discovery for patient stratification, as well as therapeutic anti-cancer targets to improve clinical outcomes. Although accumulating evidence indicates that intratumoral infiltration of immune cells has prognostic significance, limited information is available on the spatial infiltration patterns of immune cells within intratumoral regions. This study aimed to understand the intratumoral heterogeneity and spatial distribution of immune cell infiltrates associated with cell phenotypes and prognosis in head and neck squamous cell carcinoma (HNSCC).MethodsA total of 88 specimens of oropharyngeal squamous cell carcinoma, categorized into discovery (n = 38) and validation cohorts (n = 51), were analyzed for immune contexture by multiplexed immunohistochemistry (IHC) and image cytometry-based quantification. Tissue segmentation was performed according to a mathematical morphological approach using neoplastic cell IHC images to dissect intratumoral regions into tumor cell nests versus intratumoral stroma.ResultsTissue segmentation revealed heterogeneity in intratumoral T cells, varying from tumor cell nest-polarized to intratumoral stroma-polarized distributions. Leukocyte composition analysis revealed higher ratios of TH1/TH2 in tumor cell nests with higher percentages of helper T cells, B cells, and CD66b+ granulocytes within intratumoral stroma. A discovery and validation approach revealed a high density of programmed death receptor-1 (PD-1)+ helper T cells in tumor cell nests as a negative prognostic factor for short overall survival. CD163+ tumor-associated macrophages (TAM) provided the strongest correlation with PD-1+ helper T cells, and cases with a high density of PD-1+ helper T cells and CD163+ TAM had a significantly shorter overall survival than other cases.ConclusionThis study reveals the significance of analyzing intratumoral cell nests and reports that an immune microenvironment with a high density of PD-1+ helper T cells in tumoral cell nests is a poor prognostic factor for HNSCC.


Cancer ◽  
1998 ◽  
Vol 83 (5) ◽  
pp. 858-866 ◽  
Author(s):  
Shoji Natsugoe ◽  
James Mueller ◽  
Hubert J. Stein ◽  
Marcus Feith ◽  
Heinz H�fler ◽  
...  

2013 ◽  
Vol 182 (2) ◽  
pp. 516-528 ◽  
Author(s):  
Chang-Han Chen ◽  
Hui-Ching Chuang ◽  
Chao-Cheng Huang ◽  
Fu-Min Fang ◽  
Hsuan-Ying Huang ◽  
...  

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