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鉴定和验证肝内胆管细胞癌的炎症亚型。

Identification and validation of inflammatory subtypes in intrahepatic cholangiocellular carcinoma.

机构信息

Nankai University School of Medicine, Nankai University, Tianjin, China.

Faculty of Hepato-Pancreato-Biliary Surgery, Chinese PLA General Hospital, Beijing, China.

出版信息

J Transl Med. 2024 Aug 5;22(1):730. doi: 10.1186/s12967-024-05529-5.

DOI:10.1186/s12967-024-05529-5
PMID:39103879
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11302004/
Abstract

BACKGROUND

Inflammation plays a critical role in tumor development. Inflammatory cell infiltration and inflammatory mediator synthesis cause changes in the tumor microenvironment (TME) in several cancers, especially in intrahepatic cholangiocellular carcinoma (ICC). However, methods to ascertain the inflammatory state of patients using reliable biomarkers are still being explored.

METHOD

We retrieved the RNA sequencing and somatic mutation analyses results and the clinical characteristics of 244 patients with ICC from published studies. We performed consensus clustering to identify the molecular subtypes associated with inflammation. We compared the prognostic patterns, clinical characteristics, somatic mutation profiles, and immune cell infiltration patterns across inflammatory subtypes. We performed quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) to confirm gene expression. We performed logistic regression analyses to construct a nomogram predicting the inflammatory status of patients with ICC.

RESULTS

Our results confirmed that ICC can be categorized into an inflammation-high subtype (IHS) and an inflammation-low subtype (ILS). Patients from each group had distinct prognosis, clinical characteristics, and TME composition. Patients with ICC in the IHS group showed poorer prognosis owing to the immunosuppressive microenvironment and high frequency of KRAS and TP53 mutations. Cancer-associated fibroblast (CAF)-derived COLEC11 reduced myeloid inflammatory cell infiltration and attenuated inflammatory responses. The results of qRT-PCR and IHC experiments confirmed that COLEC11 expression levels were significantly reduced in tumor tissues compared to those in paracancerous tissues. Patients with ICC in the IHS group were more likely to respond to treatment with immune checkpoint inhibitors (ICIs) owing to their higher tumor mutational burden (TMB) scores, tumor neoantigen burden (TNB) scores, neoantigen counts, and immune checkpoint expression levels. Finally, we developed a nomogram to effectively predict the inflammatory status of patients with ICC based on their clinical characteristics and inflammatory gene expression levels. We evaluated the calibration, discrimination potential, and clinical utility of the nomogram.

CONCLUSION

The inflammatory response in IHS is primarily induced by myeloid cells. COLEC11 can reduce the infiltration level of this group of cells, and myeloid inflammatory cells may be a novel target for ICC treatment. We developed a novel nomogram that could effectively predict the inflammatory state of patients with ICC, which will be useful for guiding individualized treatment plans.

摘要

背景

炎症在肿瘤发展中起着关键作用。炎症细胞浸润和炎症介质合成导致几种癌症(尤其是肝内胆管细胞癌 [ICC])的肿瘤微环境 [TME] 发生变化。然而,使用可靠的生物标志物确定患者炎症状态的方法仍在探索中。

方法

我们从已发表的研究中检索了 244 例 ICC 患者的 RNA 测序和体细胞突变分析结果及临床特征。我们进行了共识聚类以确定与炎症相关的分子亚型。我们比较了炎症亚型之间的预后模式、临床特征、体细胞突变谱和免疫细胞浸润模式。我们进行了定量实时聚合酶链反应(qRT-PCR)和免疫组织化学(IHC)以验证基因表达。我们进行了逻辑回归分析以构建预测 ICC 患者炎症状态的列线图。

结果

我们的结果证实 ICC 可分为炎症高亚型(IHS)和炎症低亚型(ILS)。来自每个组的患者具有不同的预后、临床特征和 TME 组成。IHS 组的 ICC 患者由于免疫抑制微环境和 KRAS 和 TP53 突变频率高,预后较差。源自癌症相关成纤维细胞(CAF)的 COLEC11 减少了髓样炎症细胞浸润并减弱了炎症反应。qRT-PCR 和 IHC 实验的结果证实,与癌旁组织相比,肿瘤组织中 COLEC11 的表达水平明显降低。由于较高的肿瘤突变负担(TMB)评分、肿瘤新抗原负担(TNB)评分、新抗原计数和免疫检查点表达水平,IHS 组的 ICC 患者更有可能对免疫检查点抑制剂(ICI)治疗产生反应。最后,我们根据患者的临床特征和炎症基因表达水平开发了一种列线图,以有效预测 ICC 患者的炎症状态。我们评估了该列线图的校准、区分潜力和临床实用性。

结论

IHS 中的炎症反应主要由髓样细胞引起。COLEC11 可降低该组细胞的浸润水平,髓样炎症细胞可能成为 ICC 治疗的新靶点。我们开发了一种新的列线图,可以有效地预测 ICC 患者的炎症状态,这将有助于指导个体化治疗计划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/f887d4d298fc/12967_2024_5529_Fig7_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/4553e1676252/12967_2024_5529_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/f887d4d298fc/12967_2024_5529_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/4a6a4bc4e7d3/12967_2024_5529_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/52a274b684d5/12967_2024_5529_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/ddab24ef23a4/12967_2024_5529_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/fda367cebcad/12967_2024_5529_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/979833a7ee78/12967_2024_5529_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/4553e1676252/12967_2024_5529_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c097/11302004/f887d4d298fc/12967_2024_5529_Fig7_HTML.jpg

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