Association between radiomics features of DCE-MRI and CD8 <sup>+</sup> and CD4 <sup>+</sup> TILs in advanced gastric cancer

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Abstract

Objective: The aim of this investigation was to explore the correlation between the levels of tumor-infiltrating CD8 ⁺ and CD4 ⁺ T cells and the quantitative pharmacokinetic parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced gastric cancer.

Methods: We retrospectively analyzed the data of 103 patients with histopathologically confirmed advanced gastric cancer (AGC). Three pharmacokinetic parameters, K _ep, K ^trans, and V _e, and their radiomics characteristics were obtained by Omni Kinetics software. Immunohistochemical staining was used to determine CD4 ⁺ and CD8 ⁺ TILs. Statistical analysis was subsequently performed to assess the correlation between radiomics characteristics and CD4 ⁺ and CD8 ⁺ TIL density.

Results: All patients included in this study were finally divided into either a CD8 ⁺ TILs low-density group ( n = 51) (CD8 ⁺ TILs < 138) or a high-density group ( n = 52) (CD8 ⁺ TILs ≥ 138), and a CD4 ⁺ TILs low-density group ( n = 51) (CD4 ⁺ TILs < 87) or a high-density group ( n = 52) (CD4 ⁺ TILs ≥ 87). ClusterShade and Skewness based on K _ep and Skewness based on K ^trans both showed moderate negative correlation with CD8 ⁺ TIL levels ( r = 0.630–0.349, p < 0.001), with ClusterShade based on K _ep having the highest negative correlation ( r = −0.630, p < 0.001). Inertia-based K _ep showed a moderate positive correlation with the CD4 ⁺ TIL level ( r = 0.549, p < 0.001), and the Correlation based on K _ep showed a moderate negative correlation with the CD4 ⁺ TIL level, which also had the highest correlation coefficient ( r = −0.616, p < 0.001). The diagnostic efficacy of the above features was assessed by ROC curves. For CD8 ⁺ TILs, ClusterShade of K _ep had the highest mean area under the curve (AUC) (0.863). For CD4 ⁺ TILs, the Correlation of K _ep had the highest mean AUC (0.856).

Conclusion: The radiomics features of DCE-MRI are associated with the expression of tumor-infiltrating CD8 ⁺ and CD4 ⁺ T cells in AGC, which have the potential to noninvasively evaluate the expression of CD8 ⁺ and CD4 ⁺ TILs in AGC patients.

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Radiomics, the high-throughput mining of quantitative image features from standard-of-care medical imaging that enables data to be extracted and applied within clinical-decision support systems to improve diagnostic, prognostic, and predictive accuracy, is gaining importance in cancer research. Radiomic analysis exploits sophisticated image analysis tools and the rapid development and validation of medical imaging data that uses image-based signatures for precision diagnosis and treatment, providing a powerful tool in modern medicine. Herein, we describe the process of radiomics, its pitfalls, challenges, opportunities, and its capacity to improve clinical decision making, emphasizing the utility for patients with cancer. Currently, the field of radiomics lacks standardized evaluation of both the scientific integrity and the clinical relevance of the numerous published radiomics investigations resulting from the rapid growth of this area. Rigorous evaluation criteria and reporting guidelines need to be established in order for radiomics to mature as a discipline. Herein, we provide guidance for investigations to meet this urgent need in the field of radiomics.

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Gastric cancer is the fifth most common cancer and the third most common cause of cancer death globally. Risk factors for the condition include Helicobacter pylori infection, age, high salt intake, and diets low in fruit and vegetables. Gastric cancer is diagnosed histologically after endoscopic biopsy and staged using CT, endoscopic ultrasound, PET, and laparoscopy. It is a molecularly and phenotypically highly heterogeneous disease. The main treatment for early gastric cancer is endoscopic resection. Non-early operable gastric cancer is treated with surgery, which should include D2 lymphadenectomy (including lymph node stations in the perigastric mesentery and along the celiac arterial branches). Perioperative or adjuvant chemotherapy improves survival in patients with stage 1B or higher cancers. Advanced gastric cancer is treated with sequential lines of chemotherapy, starting with a platinum and fluoropyrimidine doublet in the first line; median survival is less than 1 year. Targeted therapies licensed to treat gastric cancer include trastuzumab (HER2-positive patients first line), ramucirumab (anti-angiogenic second line), and nivolumab or pembrolizumab (anti-PD-1 third line).

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Anne van der Leun, Daniela S Thommen, Ton Schumacher (2020)

The T cell infiltrates that are formed in human cancers are a modifier of natural disease progression and also determine the probability of clinical response to cancer immunotherapies. Recent technological advances that allow the single-cell analysis of phenotypic and transcriptional states have revealed a vast heterogeneity of intratumoural T cell states, both within and between patients, and the observation of this heterogeneity makes it critical to understand the relationship between individual T cell states and therapy response. This Review covers our current knowledge of the T cell states that are present in human tumours and the role that different T cell populations have been hypothesized to play within the tumour microenvironment, with a particular focus on CD8+ T cells. The three key models that are discussed herein are as follows: (1) the dysfunction of T cells in human cancer is associated with a change in T cell functionality rather than inactivity; (2) antigen recognition in the tumour microenvironment is an important driver of T cell dysfunctionality and the presence of dysfunctional T cells can hence be used as a proxy for the presence of a tumour-reactive T cell compartment; (3) a less dysfunctional population of tumour-reactive T cells may be required to drive a durable response to T cell immune checkpoint blockade.

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Author and article information

Contributors

Huizhen Huang: URI : https://loop.frontiersin.org/people/2013937/overview

Zhiheng Li: URI : https://loop.frontiersin.org/people/1407847/overview

Journal

Journal ID (nlm-ta): Pathol Oncol Res

Journal ID (iso-abbrev): Pathol Oncol Res

Journal ID (publisher-id): Pathol. Oncol. Res.

Title: Pathology and Oncology Research

Publisher: Frontiers Media S.A.

ISSN (Print): 1219-4956

ISSN (Electronic): 1532-2807

Publication date (Electronic): 05 June 2023

Publication date Collection: 2023

Volume: 29

Electronic Location Identifier: 1611001

Affiliations

[1] ¹ Shaoxing of Medicine , Shaoxing University , Shaoxing, China

[2] ² Department of Radiology , Anhui Provincial Hospital , Hefei, China

[3] ³ Department of Radiology , Shaoxing People’s Hospital , Shaoxing, China

[4] ⁴ Country Department of Pathology , Shaoxing People’s Hospital , Shaoxing, China

[5] ⁵ The First Affiliated Hospital of Shaoxing University , Shaoxing, China

Author notes

Edited by: Anna Sebestyén, Semmelweis University, Hungary

*Correspondence: Zengxin Lu, luzx777@ 123456163.com

Article

Publisher ID: 1611001

DOI: 10.3389/pore.2023.1611001

PMC ID: 10277864

PubMed ID: 37342362

SO-VID: d2234731-8dc4-4bd2-8fc5-b6f0d85b5d79

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 07 December 2022

Date accepted : 24 May 2023

Funding

This work was made possible thanks to funding from the General Project of Zhejiang Province Health Science and Technology Plan (grant numbers, 2021KY1140, 2021KY1150, 2022KY1296, and 2022KY1291).

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