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基于人工智能的子宫内膜癌三级淋巴结构空间分析及其临床意义

Artificial intelligence-based spatial analysis of tertiary lymphoid structures and clinical significance for endometrial cancer.

作者信息

Suzuki Haruka, Hamada Kohei, Hamanishi Junzo, Ueda Akihiko, Murakami Ryusuke, Taki Mana, Mizuno Rin, Watanabe Koichi, Sato Hanako, Hosoe Yuko, Ito Hiroaki, Yamanoi Koji, Yoshitomi Hiroyuki, Kakiuchi Nobuyuki, Yamaguchi Ken, Matsumura Noriomi, Ogawa Seishi, Ueno Hideki, Mandai Masaki

机构信息

Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan.

Department of Obstetrics and Gynecology, Kindai University, Osaka, Japan.

出版信息

Cancer Immunol Immunother. 2025 Feb 1;74(3):84. doi: 10.1007/s00262-024-03929-6.

DOI:10.1007/s00262-024-03929-6
PMID:39891665
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11787133/
Abstract

With the incorporation of immune checkpoint inhibitors into the treatment of endometrial cancer (EC), a deeper understanding of the tumor immune microenvironment is critical. Tertiary lymphoid structures (TLSs) are considered favorable prognostic factors for EC, but the significance of their spatial distribution remains unclear. B cell receptor repertoire analysis performed using six TLS samples located at various distances from the tumor showed that TLSs in distal areas had more shared B cell clones with tumor-infiltrating lymphocytes. To comprehensively investigate the distribution of TLSs, we developed an artificial intelligence model to detect TLSs and determine their spatial locations in whole-slide images. Our model effectively quantified TLSs, and TLSs were detected in 69% of the patients with EC. We identified them as proximal or distal to the tumor margin and demonstrated that patients with distal TLSs (dTLSs) had significantly prolonged overall survival and progression-free survival (PFS) across multiple cohorts [hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.36-0.88; p = 0.01 for overall survival; HR, 0.58; 95% CI, 0.40-0.84; p = 0.004 for PFS]. When analyzed by molecular subtype, patients with dTLSs in the copy-number-high EC subtype had significantly longer PFS (HR, 0.51; 95% CI, 0.29-0.91; p = 0.02). Moreover, patients with dTLSs had a higher response rate to immune checkpoint inhibitors (87.5 vs. 41.7%) and a trend toward improved PFS. Our findings indicate that the functions and prognostic implications of TLSs may vary with their locations, and dTLSs may serve as prognostic factors and predictors of treatment efficacy. This may facilitate personalized therapy for patients with EC.

摘要

随着免疫检查点抑制剂被纳入子宫内膜癌(EC)的治疗,深入了解肿瘤免疫微环境至关重要。三级淋巴结构(TLSs)被认为是EC的有利预后因素,但其空间分布的意义仍不清楚。对位于距肿瘤不同距离的六个TLS样本进行的B细胞受体组库分析表明,远端区域的TLSs与肿瘤浸润淋巴细胞有更多共享的B细胞克隆。为了全面研究TLSs的分布,我们开发了一种人工智能模型来检测TLSs并确定其在全切片图像中的空间位置。我们的模型有效地量化了TLSs,并且在69%的EC患者中检测到了TLSs。我们将它们确定为肿瘤边缘的近端或远端,并证明在多个队列中,远端TLSs(dTLSs)患者的总生存期和无进展生存期(PFS)显著延长[风险比(HR),0.56;95%置信区间(CI),0.36 - 0.88;总生存期p = 0.01;HR,0.58;95% CI,0.40 - 0.84;PFS p = 0.004]。按分子亚型分析时,拷贝数高的EC亚型中具有dTLSs的患者的PFS显著更长(HR,0.51;95% CI,0.29 - 0.91;p = 0.02)。此外,具有dTLSs的患者对免疫检查点抑制剂的反应率更高(87.5%对41.7%),并且有PFS改善的趋势。我们的研究结果表明,TLSs的功能和预后意义可能因其位置而异,并且dTLSs可能作为预后因素和治疗疗效的预测指标。这可能有助于为EC患者提供个性化治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/ccf1bd9a3e0e/262_2024_3929_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/cc26bf50eb13/262_2024_3929_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/ccf1bd9a3e0e/262_2024_3929_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/cc26bf50eb13/262_2024_3929_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/0ff475521985/262_2024_3929_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/03ccec8beba0/262_2024_3929_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/81dce1d02b4a/262_2024_3929_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec8a/11787133/ccf1bd9a3e0e/262_2024_3929_Fig5_HTML.jpg

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