Tissue‐matched analysis of MRI evaluating the tumor infiltrating lymphocytes in hepatocellular carcinoma

Tumor‐infiltrating lymphocytes (TILs) play critical roles in the tumor microenvironment and immunotherapy response. This study aims to explore the feasibility of multi‐parametric magnetic resonance imaging (MRI) in evaluating TILs and to develop an evaluation model that considers spatial heterogenei...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of cancer Ročník 156; číslo 8; s. 1634 - 1643
Hlavní autoři: Huang, Mengqi, Song, Chenyu, Zhou, Xiaoqi, Wang, Huanjun, Lin, Yingyu, Wang, Jifei, Cai, Huasong, Wang, Meng, Peng, Zhenpeng, Dong, Zhi, Feng, Shi‐Ting
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, USA John Wiley & Sons, Inc 15.04.2025
Wiley Subscription Services, Inc
Témata:
ISSN:0020-7136, 1097-0215, 1097-0215
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Tumor‐infiltrating lymphocytes (TILs) play critical roles in the tumor microenvironment and immunotherapy response. This study aims to explore the feasibility of multi‐parametric magnetic resonance imaging (MRI) in evaluating TILs and to develop an evaluation model that considers spatial heterogeneity. Multi‐parametric MRI was performed on hepatocellular carcinoma (HCC) mice (N = 28). Three‐dimensional (3D) printing was employed for tissue sampling, to match the multi‐parametric MRI data with tumor tissues, followed by flow cytometry analysis and next‐generation RNA‐sequencing. Pearson's correlation, multivariate logistic regression, and receiver operating characteristic (ROC) curve analyses were utilized to model TIL‐related MRI parameters. MRI quantitative parameters, including T1 relaxation times and perfusion, were correlated with the infiltration of leukocytes, T‐cells, CD4+ T‐cells, CD8+ T‐cells, PD1 + CD8+ T‐cells, B‐cells, macrophages, and regulatory T‐cells (correlation coefficients ranged from −0.656 to 0.482, p <.05) in tumor tissues. TILs were clustered into inflamed and non‐inflamed subclasses, with the proportion of T‐cells, CD8+ T‐cells, and PD1 + CD8+ T‐cells significantly higher in the inflamed group compared to the non‐inflamed group (43.37% vs. 25.45%, 50.83% vs. 34.90%, 40.45% vs. 29.47%, respectively; p <.001). The TIL evaluation model, based on the Z‐score combining Kep and T1post, was able to distinguish between these subgroups, yielding an area under the curve of 0.816 (95% confidence interval 0.721–0.910) and a cut‐off value of −0.03 (sensitivity 68.4%, specificity 91.3%). Additionally, the Z‐score was related to the gene expression of T‐cell activation, chemokine production, and cell adhesion. The tissue‐matched analysis of multi‐parametric MRI offers a feasible method of regional evaluation and can distinguish between TIL subclasses. What's new? Increasing evidence suggests that the evaluation of tumor‐infiltrating lymphocytes both at baseline and throughout cancer therapy can be valuable for predicting and monitoring treatment responses. Tumor heterogeneity however complicates the assessment of tumor‐infiltrating lymphocytes. In this study, the authors used an animal model and three‐dimensional printing technology to achieve guided tumor spatial segmentation and regional evaluation of tumor‐infiltrating lymphocytes. They present a feasible, non‐invasive magnetic resonance imaging‐based model for evaluating tumor‐infiltrating lymphocytes in hepatocellular carcinoma that takes spatial heterogeneity into account and could potentially inform the immunotherapy response in patients.
Bibliografie:Mengqi Huang and Chenyu Song have contributed equally and considered as co‐first author.
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0020-7136
1097-0215
1097-0215
DOI:10.1002/ijc.35281