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基于甲基化 SEPT9 和肿瘤内 IL-10 Tregs 浸润的结直肠癌临床结局预测列线图。

Predictive nomogram of the clinical outcomes of colorectal cancer based on methylated SEPT9 and intratumoral IL-10 Tregs infiltration.

机构信息

Nankai University School of Medicine, Nankai University, Tianjin, 300071, People's Republic of China.

Department of Pathology, Tianjin Union Medical Center, Tianjin, 300121, People's Republic of China.

出版信息

J Transl Med. 2024 Sep 27;22(1):861. doi: 10.1186/s12967-024-05635-4.

DOI:10.1186/s12967-024-05635-4
PMID:39334238
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11430755/
Abstract

BACKGROUND

Gene methylation and the immune-related tumor microenvironment (TME) are highly correlated in tumor progression and therapeutic efficacy. Although both of them can be used to predict the clinical outcomes of colorectal cancer (CRC) patients, their predictive value is still unsatisfactory. Whether a combination risk model comprising these two prediction parameters performs better predictive effectiveness than independent factor is still unclear. Methylated Septin9 (mSEPT9) is an early diagnosis biomarker of CRC, in this study, we aimed to investigate mSEPT9-related biomarkers of immunosuppressive TME and identify the value of the combination risk model in predicting the clinical outcomes of CRC.

METHODS

Immunofluorescence staining was performed to clarify the correlation between intratumoral IL-10 Treg infiltration and mSEPT9 in peripheral blood. Survival time, response to 5-fluorouracil (5-FU)-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis were analyzed in study (197 CRC samples) and validation (195 CRC samples) sets to evaluate the efficacy of combination risk model. Potential mechanisms were explored by mRNA sequencing.

RESULTS

Hypermethylated SEPT9 in the peripheral blood of patients with CRC (stage I-III, and stage IV with resectable M1) before radical resection was positively correlated with high intratumoral IL-10 Treg infiltration. The high-risk model revealed poor overall survival and progression-free survival, inferior therapeutic response to 5-FU-based chemotherapy and PD-1 blockade, and high probability of recurrence or metastasis. The underlying mechanisms may be associated with the increase in mSEPT9 and mediation of IL-10 via methionine metabolic reprogramming-induced infiltration of IL-10 Tregs in the TME, which promotes tumor progression and resistance to 5-FU-based chemotherapy and PD-1 blockade.

CONCLUSIONS

The combination risk model of peripheral mSETP9 and intratumoral IL-10 Treg infiltration in CRC can effectively predict prognosis, responsiveness to 5-FU-based chemotherapy and PD-1 blockade, and the probability of recurrence or metastasis. Therefore, this model can be used for precision treatment of CRC.

摘要

背景

基因甲基化和与免疫相关的肿瘤微环境(TME)在肿瘤进展和治疗效果中高度相关。尽管它们都可用于预测结直肠癌(CRC)患者的临床结局,但它们的预测价值仍不理想。包含这两个预测参数的组合风险模型是否比独立因素具有更好的预测效果尚不清楚。甲基化 Septin9(mSEPT9)是 CRC 的早期诊断生物标志物,本研究旨在探讨 mSEPT9 相关的免疫抑制性 TME 生物标志物,并确定组合风险模型在预测 CRC 临床结局中的价值。

方法

通过免疫荧光染色来阐明肿瘤内 IL-10 Treg 浸润与外周血中 mSEPT9 之间的相关性。在研究(197 例 CRC 样本)和验证(195 例 CRC 样本)组中分析生存时间、对 5-氟尿嘧啶(5-FU)为基础的化疗和 PD-1 阻断的反应以及复发或转移的概率,以评估组合风险模型的疗效。通过 mRNA 测序探索潜在机制。

结果

在根治性切除前的 CRC 患者(I-III 期和可切除 M1 期 IV 期)的外周血中,SEPT9 高甲基化与肿瘤内高 IL-10 Treg 浸润呈正相关。高危模型显示总体生存率和无进展生存率较差,对 5-FU 为基础的化疗和 PD-1 阻断的治疗反应较差,复发或转移的概率较高。潜在机制可能与 mSEPT9 的增加以及通过蛋氨酸代谢重编程诱导 TME 中 IL-10 Treg 浸润介导的 IL-10 增加有关,这促进了肿瘤的进展和对 5-FU 为基础的化疗和 PD-1 阻断的耐药性。

结论

CRC 外周血 mSETP9 与肿瘤内 IL-10 Treg 浸润的组合风险模型可有效预测预后、对 5-FU 为基础的化疗和 PD-1 阻断的反应以及复发或转移的概率。因此,该模型可用于 CRC 的精准治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/9a41ef76aaf4/12967_2024_5635_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/86c167ef8515/12967_2024_5635_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/ae98e679eaaf/12967_2024_5635_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/ba60ac06273c/12967_2024_5635_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/3c8c1c941ef8/12967_2024_5635_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/876407d8d983/12967_2024_5635_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/9a41ef76aaf4/12967_2024_5635_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/86c167ef8515/12967_2024_5635_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/ae98e679eaaf/12967_2024_5635_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/ba60ac06273c/12967_2024_5635_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/3c8c1c941ef8/12967_2024_5635_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/876407d8d983/12967_2024_5635_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d646/11430755/9a41ef76aaf4/12967_2024_5635_Fig6_HTML.jpg

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