Literature DB >> 26256482

Immunohistochemical biomarkers and FDG uptake on PET/CT in head and neck squamous cell carcinoma.

Gregers Brünnich Rasmussen1, Ivan R Vogelius1, Jacob H Rasmussen1, Lisa Schumaker2, Olga Ioffe3, Kevin Cullen2, Barbara Malene Fischer4, Marianne Hamilton Therkildsen5, Lena Specht1, Søren M Bentzen1,6,2.   

Abstract

BACKGROUND: There is an exciting complementarity between the spatial resolution provided by molecular imaging of a single, often unspecific, biomarker on one hand and the more detailed biological profile achievable from a diagnostic biopsy using a panel of immunohistochemical (IHC) markers on the other. A number of previous studies have shown a relationship between glucose transport protein expression and 18F-Fludeoxyglucose (FDG) PET uptake. Here, FDG uptake is analyzed in relation to expression of a selected panel of IHC cancer biomarkers in head and neck squamous cell carcinomas (HNSCC).
MATERIAL AND METHODS: IHC staining for Bcl-2, β-tubulin-1 and 2, p53, EGFR, Ki-67, glutathione-S-transferase-π and p16 was performed on formalin-fixed paraffin embedded diagnostic biopsies from 102 HNSCC cases treated at Rigshospitalet during 2005-2009. The proportion of positive cells was used for analyses, except p16, which was scored according to EORTC guidelines. In all cases, maximal FDG standardized uptake value (SUV) metrics were extracted for the primary tumor, TSUVmax. Univariate linear regression and multiple linear regression of TSUVmax versus IHC markers were performed.
RESULTS: In univariate analyses, TSUVmax showed negative associations with Bcl-2 (p = 0.002) and p16 (p = 0.005) indices and positive association with β-tubulin-1 index (p = 0.003). On multivariate analysis, TSUVmax remained associated with β-tubulin-1 (p = 0.009), Bcl-2 (p = 0.03) and p16 (p = 0.03). All correlations had r-squared < 0.3.
CONCLUSION: Statistically significant correlations were observed between the expression of IHC biomarkers and maximum FDG uptake in the primary tumor.

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Year:  2015        PMID: 26256482     DOI: 10.3109/0284186X.2015.1062539

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  12 in total

1.  Histogram Analysis Parameters Derived from Conventional T1- and T2-Weighted Images Can Predict Different Histopathological Features Including Expression of Ki67, EGFR, VEGF, HIF-1α, and p53 and Cell Count in Head and Neck Squamous Cell Carcinoma.

Authors:  Hans Jonas Meyer; Leonard Leifels; Gordian Hamerla; Anne Kathrin Höhn; Alexey Surov
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

2.  Associations Between [18F]FDG-PET and Complex Histopathological Parameters Including Tumor Cell Count and Expression of KI 67, EGFR, VEGF, HIF-1α, and p53 in Head and Neck Squamous Cell Carcinoma.

Authors:  Alexey Surov; Hans Jonas Meyer; Anne-Kathrin Höhn; Karsten Winter; Osama Sabri; Sandra Purz
Journal:  Mol Imaging Biol       Date:  2019-04       Impact factor: 3.488

3.  Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

Authors:  Alexey Surov; Hans Jonas Meyer; Andreas Wienke
Journal:  Transl Oncol       Date:  2018-03-03       Impact factor: 4.243

4.  CT Texture Analysis-Correlations With Histopathology Parameters in Head and Neck Squamous Cell Carcinomas.

Authors:  Hans-Jonas Meyer; Gordian Hamerla; Anne Kathrin Höhn; Alexey Surov
Journal:  Front Oncol       Date:  2019-05-28       Impact factor: 6.244

5.  Associations between Histogram Analysis Parameters Derived from DCE-MRI and Histopathological Features including Expression of EGFR, p16, VEGF, Hif1-alpha, and p53 in HNSCC.

Authors:  Hans Jonas Meyer; Leonard Leifels; Gordian Hamerla; Anne Kathrin Höhn; Alexey Surov
Journal:  Contrast Media Mol Imaging       Date:  2019-01-02       Impact factor: 3.161

6.  Associations between FDG-PET and Ki 67-index in head and neck cancer: A meta-analysis.

Authors:  Hans-Jonas Meyer; Peter Gundermann; Alexey Surov
Journal:  Medicine (Baltimore)       Date:  2019-10       Impact factor: 1.889

Review 7.  Combining Diagnostic Imaging and Pathology for Improving Diagnosis and Prognosis of Cancer.

Authors:  Orazio Schillaci; Manuel Scimeca; Nicola Toschi; Rita Bonfiglio; Nicoletta Urbano; Elena Bonanno
Journal:  Contrast Media Mol Imaging       Date:  2019-07-01       Impact factor: 3.161

8.  Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study.

Authors:  Noriyuki Fujima; Yukie Shimizu; Daisuke Yoshida; Satoshi Kano; Takatsugu Mizumachi; Akihiro Homma; Koichi Yasuda; Rikiya Onimaru; Osamu Sakai; Kohsuke Kudo; Hiroki Shirato
Journal:  Cancers (Basel)       Date:  2019-06-10       Impact factor: 6.639

9.  Combined Metabolo-Volumetric Parameters of 18F-FDG-PET and MRI Can Predict Tumor Cellularity, Ki67 Level and Expression of HIF 1alpha in Head and Neck Squamous Cell Carcinoma: A Pilot Study.

Authors:  Alexey Surov; Hans Jonas Meyer; Anne Kathrin Höhn; Osama Sabri; Sandra Purz
Journal:  Transl Oncol       Date:  2018-09-18       Impact factor: 4.243

Review 10.  A review on immunohistochemical and histopathologic validation in PET-CT findings with consideration to microRNAs.

Authors:  Marius-Ioan Bădan; Eduard-Alexandru Bonci; Doina Piciu
Journal:  Med Pharm Rep       Date:  2019-10-25
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