Dataset Information

Magnetic Resonance Imaging of Tumor-Associated Macrophages: Clinical Translation.

ABSTRACT: Purpose: Tumor-associated macrophages (TAMs) in malignant tumors have been linked to tumor aggressiveness and represent a new target for cancer immunotherapy. As new TAM-targeted immunotherapies are entering clinical trials, it is important to detect and quantify TAM with noninvasive imaging techniques. The purpose of this study was to determine if ferumoxytol-enhanced MRI can detect TAM in lymphomas and bone sarcomas of pediatric patients and young adults.Experimental Design: In a first-in-patient, Institutional Review Board-approved prospective clinical trial, 25 pediatric and young adult patients with lymphoma or bone sarcoma underwent ferumoxytol-enhanced MRI. To confirm ferumoxytol enhancement, five pilot patients (two lymphoma and three bone sarcoma) underwent pre- and postcontrast MRI. Subsequently, 20 patients (10 lymphoma and 10 bone sarcoma) underwent ferumoxytol-enhanced MRI 24 to 48 hours after i.v. injection, followed by tumor biopsy/resection and macrophage staining. To determine if ferumoxytol-MRI can differentiate tumors with different TAM content, we compared T2* relaxation times of lymphomas and bone sarcomas. Tumor T2* values of 20 patients were correlated with CD68+ and CD163+ TAM quantities on histopathology.Results: Significant ferumoxytol tumor enhancement was noted on postcontrast scans compared with precontrast scans (P = 0.036). Bone sarcomas and lymphomas demonstrated significantly different MRI enhancement and TAM density (P < 0.05). Within each tumor group, T2* signal enhancement on MR images correlated significantly with the density of CD68+ and CD163+ TAM (P < 0.05).Conclusions: Ferumoxytol-enhanced MRI is immediately clinically applicable and could be used to stratify patients with TAM-rich tumors to immune-targeted therapies and to monitor tumor response to these therapies. Clin Cancer Res; 24(17); 4110-8. ©2018 AACR.

SUBMITTER: Aghighi M

PROVIDER: S-EPMC6125171 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Magnetic Resonance Imaging of Tumor-Associated Macrophages: Clinical Translation.

Aghighi Maryam M Theruvath Ashok J AJ Pareek Anuj A Pisani Laura L LL Alford Raphael R Muehe Anne M AM Sethi Tarsheen K TK Holdsworth Samantha J SJ Hazard Florette K FK Gratzinger Dita D Luna-Fineman Sandra S Advani Ranjana R Spunt Sheri L SL Daldrup-Link Heike E HE

Clinical cancer research : an official journal of the American Association for Cancer Research 20180515 17

<b>Purpose:</b> Tumor-associated macrophages (TAMs) in malignant tumors have been linked to tumor aggressiveness and represent a new target for cancer immunotherapy. As new TAM-targeted immunotherapies are entering clinical trials, it is important to detect and quantify TAM with noninvasive imaging techniques. The purpose of this study was to determine if ferumoxytol-enhanced MRI can detect TAM in lymphomas and bone sarcomas of pediatric patients and young adults.<b>Experimental Design:</b> In a ...[more]

PMID: 29764855

Similar Datasets

Project description:BACKGROUND:We sought to investigate associations between dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) features and tumor-infiltrating lymphocytes (TILs) in breast cancer, as well as to study if MRI features are complementary to molecular markers of TILs. METHODS:In this retrospective study, we extracted 17 computational DCE-MRI features to characterize tumor and parenchyma in The Cancer Genome Atlas cohort (n?=?126). The percentage of stromal TILs was evaluated on H&E-stained histological whole-tumor sections. We first evaluated associations between individual imaging features and TILs. Multiple-hypothesis testing was corrected by the Benjamini-Hochberg method using false discovery rate (FDR). Second, we implemented LASSO (least absolute shrinkage and selection operator) and linear regression nested with tenfold cross-validation to develop an imaging signature for TILs. Next, we built a composite prediction model for TILs by combining imaging signature with molecular features. Finally, we tested the prognostic significance of the TIL model in an independent cohort (I-SPY 1; n?=?106). RESULTS:Four imaging features were significantly associated with TILs (P?<?0.05 and FDR?<?0.2), including tumor volume, cluster shade of signal enhancement ratio (SER), mean SER of tumor-surrounding background parenchymal enhancement (BPE), and proportion of BPE. Among molecular and clinicopathological factors, only cytolytic score was correlated with TILs (??=?0.51; 95% CI, 0.36-0.63; P?=?1.6E-9). An imaging signature that linearly combines five features showed correlation with TILs (??=?0.40; 95% CI, 0.24-0.54; P?=?4.2E-6). A composite model combining the imaging signature and cytolytic score improved correlation with TILs (??=?0.62; 95% CI, 0.50-0.72; P?=?9.7E-15). The composite model successfully distinguished low vs high, intermediate vs high, and low vs intermediate TIL groups, with AUCs of 0.94, 0.76, and 0.79, respectively. During validation (I-SPY 1), the predicted TILs from the imaging signature separated patients into two groups with distinct recurrence-free survival (RFS), with log-rank P?=?0.042 among triple-negative breast cancer (TNBC). The composite model further improved stratification of patients with distinct RFS (log-rank P?=?0.0008), where TNBC with no/minimal TILs had a worse prognosis. CONCLUSIONS:Specific MRI features of tumor and parenchyma are associated with TILs in breast cancer, and imaging may play an important role in the evaluation of TILs by providing key complementary information in equivocal cases or situations that are prone to sampling bias.

Dataset Information

Magnetic Resonance Imaging of Tumor-Associated Macrophages: Clinical Translation.

Publications

Magnetic Resonance Imaging of Tumor-Associated Macrophages: Clinical Translation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets