Dataset Information

Identifying Biomarkers in Lymph Node Metastases of Esophageal Adenocarcinoma for Tumor-Targeted Imaging.

ABSTRACT: INTRODUCTION:Tumor-targeted imaging is a promising technique for the detection of lymph node metastases (LNM) and primary tumors. It remains unclear which biomarker is the most suitable target to distinguish malignant from healthy tissue in esophageal adenocarcinoma (EAC). OBJECTIVE:We performed an immunohistochemistry study to identify viable tumor markers for tumor-targeted imaging of EAC. METHODS:We used samples from 72 patients with EAC to determine the immunohistochemical expression of ten potential tumor biomarkers for EAC (carbonic anhydrase IX [CA-IX], carcinoembryonic antigen [CEA], hepatic growth factor receptor, epidermal growth factor receptor, epithelial membrane antigen [EMA], epithelial cell adhesion molecule [EpCAM], human epidermal growth factor receptor 2 [HER-2], urokinase plasminogen activator receptor, vascular endothelial growth factor-A [VEGF-A], and VEGF receptor 2). Immunohistochemistry was performed on tissue microarrays of LNM (n?=?48), primary EACs (n?=?62), fibrotic tissues (n?=?11), nonmalignant lymph nodes (n?=?24), and normal esophageal and gastric tissues (n?=?40). Tumor marker staining was scored on intensity and percentage of positive cells. RESULTS:EMA and EpCAM showed strong expression in LNM (>?95%) and primary EACs (>?95%). Significant expression was also observed for LNM and EAC using VEGF-A (85 and 92%), CEA (68 and 54%), and CA-IX (4 and 34%). The other tumor biomarkers showed expression of 0-15% for LNM and primary EAC. Except for VEGF-A, nonmalignant lymph node staining was scored as slight or absent. CONCLUSIONS:High expression rates and correlation between LNM in EAC combined with low expression rates in healthy lymph nodes and esophagus tissues were observed for EpCAM and CEA, meaning these are promising targets for tumor-targeted imaging approaches for lymph nodes in patients with EAC.

SUBMITTER: de Gouw DJJM

PROVIDER: S-EPMC7113228 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Identifying Biomarkers in Lymph Node Metastases of Esophageal Adenocarcinoma for Tumor-Targeted Imaging.

de Gouw D J J M DJJM Rijpkema M M de Bitter T J J TJJ Baart V M VM Sier C F M CFM Hernot S S van Dam G M GM Nagtegaal I D ID Klarenbeek B R BR Rosman C C van der Post R S RS

Molecular diagnosis & therapy 20200401 2

<h4>Introduction</h4>Tumor-targeted imaging is a promising technique for the detection of lymph node metastases (LNM) and primary tumors. It remains unclear which biomarker is the most suitable target to distinguish malignant from healthy tissue in esophageal adenocarcinoma (EAC).<h4>Objective</h4>We performed an immunohistochemistry study to identify viable tumor markers for tumor-targeted imaging of EAC.<h4>Methods</h4>We used samples from 72 patients with EAC to determine the immunohistochemi ...[more]

PMID: 32048177

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Project description:BackgroundThe essential roles of the tumor microenvironment (TME) have been recognized during the initiation and progression of primary lung adenocarcinoma (LUAD). The aim of the present study was to delineate the immune landscape in both primary cancer and matched lymph node metastasis from a cohort of locally advanced stage LUAD patients with distinct outcomes.MethodsFormalin-fixed, paraffin-embedded samples were collected from 36 locally advanced LUAD patients. Transcriptome data of the tumor immune microenvironment were resolved using an immune oncology panel RNA sequencing platform. Bioinformatics approaches were used to determine the differentially expressed genes (DEGs), dysregulated pathways, and immune cell fraction between patients with early recurrence (ER) and late recurrence (LR).ResultsHere, we showed that in primary cancer tissues, 23 DEGs were obtained between patients with ER and LR. Functional analysis revealed that the LR in LUAD patients may be associated with enriched gene sets belonging to the antigen presentation and MHC protein complex, innate immune response, and IFN-γ signaling pathways. Next, the transcriptome data were adopted to quantify immune cell fractions, indicating that high infiltration of mast cells and neutrophils was correlated with ER. Interestingly, similar findings were observed in metastatic lymph nodes from patients suffering from ER or LR. By analyzing the shared immune features of primary cancers and lymphatic metastases, we unraveled the prognostic value and joint utility of two DEGs, CORO1A and S100A8.ConclusionsIn LUAD, the enrichment in antigen presentation, MHC protein complex, and IFN-γ signaling, and low infiltration of neutrophils in primary or metastatic nodules may be indications for a favorable prognosis. Integrated with bioinformatics approaches, transcriptome data of immune-related genes from formalin-fixed, paraffin-embedded (FFPE) samples can effectively profile the landscape of the tumor immune microenvironment and help predict clinical outcomes.

Project description:ObjectivesTo improve clinical lymph node staging (cN-stage) in oesophageal adenocarcinoma by developing and externally validating three prediction models; one with clinical variables only, one with positron emission tomography (PET) radiomics only, and a combined clinical and radiomics model.MethodsConsecutive patients with fluorodeoxyglucose (FDG) avid tumours treated with neoadjuvant therapy between 2010 and 2016 in two international centres (n = 130 and n = 60, respectively) were included. Four clinical variables (age, gender, clinical T-stage and tumour regression grade) and PET radiomics from the primary tumour were used for model development. Diagnostic accuracy, area under curve (AUC), discrimination and calibration were calculated for each model. The prognostic significance was also assessed.ResultsThe incidence of lymph node metastases was 58% in both cohorts. The areas under the curve of the clinical, radiomics and combined models were 0.79, 0.69 and 0.82 in the developmental cohort, and 0.65, 0.63 and 0.69 in the external validation cohort, with good calibration demonstrated. The area under the curve of current cN-stage in development and validation cohorts was 0.60 and 0.66, respectively. For overall survival, the combined clinical and radiomics model achieved the best discrimination performance in the external validation cohort (X2 = 6.08, df = 1, p = 0.01).ConclusionAccurate diagnosis of lymph node metastases is crucial for prognosis and guiding treatment decisions. Despite finding improved predictive performance in the development cohort, the models using PET radiomics derived from the primary tumour were not fully replicated in an external validation cohort.Advances in knowledgeThis international study attempted to externally validate a new prediction model for lymph node metastases using PET radiomics. A model combining clinical variables and PET radiomics improved discrimination of lymph node metastases, but these results were not externally replicated.

Dataset Information

Identifying Biomarkers in Lymph Node Metastases of Esophageal Adenocarcinoma for Tumor-Targeted Imaging.

Publications

Identifying Biomarkers in Lymph Node Metastases of Esophageal Adenocarcinoma for Tumor-Targeted Imaging.

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