A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Multimodal optical, X-ray CT, and SPECT imaging of a mouse model of breast cancer lung metastasis. | LitMetric

Multimodal optical, X-ray CT, and SPECT imaging of a mouse model of breast cancer lung metastasis.

Curr Mol Med

Department of Biological Sciences, 100 Galvin Life Sciences Center, University of Notre Dame, Notre Dame, IN 46556, USA.

Published: March 2013

Tumor heterogeneity is recognized as a major issue within clinical oncology, and the concept of personalized molecular medicine is emerging as a means to mitigate this problem. Given the vast number of cancer types and subtypes, robust pre-clinical models of cancer must be studied to interrogate the molecular mechanisms involved in each scenario. In particular, mouse models of tumor metastasis are of critical importance for pre-clinical cancer research at the cancer cell molecular level. In many of these experimental systems, tumor cells are injected intravenously, and the distribution and proliferation of these cells are subsequently analyzed via ex vivo methods. These techniques require large numbers of animals coupled with time-consuming histological preparation and analysis. Herein, we demonstrate the use of two facile and noninvasive imaging techniques to enhance the study of a pre-clinical model of breast cancer metastasis in the lung. Breast cancer cells were labeled with a near-infrared fluorophore that enables their visualization. Upon injection into a living mouse, the distribution of the cells in the body was detected and measured using whole animal fluorescence imaging. X-ray computed tomography (CT) was subsequently used to provide a quantitative measure of longitudinal tumor cell accumulation in the lungs over six weeks. A nuclear probe for lung perfusion, 99mTc-MAA, was also imaged and tested during the time course using single photon emission computed tomography (SPECT). Our results demonstrate that optical fluorescence methods are useful to visualize cancer cell distribution patterns that occur immediately after injection. Longitudinal imaging with X-ray CT provides a convenient and quantitative avenue to measure tumor growth within the lung space over several weeks. Results with nuclear imaging did not show a correlation between lung perfusion (SPECT) and segmented lung volume (CT). Nevertheless, the combination of animal models and noninvasive optical and CT imaging methods provides better research tools to study cancer cell differences at the molecular level. Ultimately, the knowledge gleaned from these improved studies will aid researchers in uncovering the mechanisms mediating breast cancer metastasis, and eventually improve the treatments of patients in the clinic.

Download full-text PDF

Source
http://dx.doi.org/10.2174/1566524011313030006DOI Listing

Publication Analysis

Top Keywords

breast cancer
16
cancer cell
12
cancer
10
model breast
8
molecular level
8
cancer metastasis
8
imaging x-ray
8
computed tomography
8
weeks nuclear
8
lung perfusion
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!