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结合单细胞和批量 RNA 测序技术对甲状腺乳头状癌成纤维细胞分子特征的综合分析。

Integrated analysis of fibroblasts molecular features in papillary thyroid cancer combining single-cell and bulk RNA sequencing technology.

机构信息

Department of General Surgery, Changzheng Hospital, Navy Medical University, Shanghai, China.

Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, China.

出版信息

Front Endocrinol (Lausanne). 2022 Oct 26;13:1019072. doi: 10.3389/fendo.2022.1019072. eCollection 2022.

DOI:10.3389/fendo.2022.1019072
PMID:36387901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9643292/
Abstract

BACKGROUND

Papillary thyroid cancer (PTC) is the most common pathological type of thyroid cancer with a high incidence globally. Increasing evidence reported that fibroblasts infiltration in cancer was correlated with prognostic outcomes. However, fibroblasts related study in thyroid cancer remains deficient.

METHODS

Single-cell sequencing data of PTC were analyzed by Seurat R package to explore the ecosystem in PTC and identify fibroblasts cluster. The expression profiles and prognostic values of fibroblast related genes were assessed in TCGA dataset. A fibrosis score model was established for prognosis prediction in thyroid cancer patients. Differentially expressed genes and functional enrichment between high and low fibrosis score groups in TCGA dataset were screened. The correlation of immune cells infiltration and fibrosis score in thyroid cancer patients was explored. Expression levels and prognostic values of key fibroblast related factor were validated in clinical tissues another PTC cohort.

RESULTS

Fibroblasts were highly infiltrated in PTC and could interact with other type of cells by single-cell data analysis. 34 fibroblast related terms were differentially expressed in thyroid tumor tissues. COX regression analysis suggested that the constructed fibrosis score model was an independent prognostic predictor for thyroid cancer patients (HR = 5.17, 95%CI 2.31-11.56, P = 6.36E-05). Patients with low fibrosis scores were associated with a significantly better overall survival (OS) than those with high fibrosis scores in TCGA dataset (P = 7.659E-04). Specific immune cells infiltration levels were positively correlated with fibrosis score, including monocytes, M1 macrophages and eosinophils.

CONCLUSION

Our research demonstrated a comprehensive horizon of fibroblasts features in thyroid cancer microenvironment, which may provide potential value for thyroid cancer treatment.

摘要

背景

甲状腺癌（PTC）是最常见的甲状腺癌病理类型，全球发病率较高。越来越多的证据表明，癌症中的成纤维细胞浸润与预后结果相关。然而，甲状腺癌中成纤维细胞的相关研究仍然不足。

方法

通过 Seurat R 包分析 PTC 的单细胞测序数据，探索 PTC 中的生态系统并鉴定成纤维细胞簇。在 TCGA 数据集评估与成纤维细胞相关的基因的表达谱和预后价值。建立纤维化评分模型以预测甲状腺癌患者的预后。筛选 TCGA 数据集高纤维化评分组和低纤维化评分组之间差异表达基因和功能富集。探讨甲状腺癌患者中免疫细胞浸润与纤维化评分的相关性。验证关键成纤维细胞相关因子在临床组织和另一个 PTC 队列中的表达水平和预后价值。

结果

成纤维细胞在 PTC 中高度浸润，可以通过单细胞数据分析与其他类型的细胞相互作用。34 个与成纤维细胞相关的术语在甲状腺肿瘤组织中差异表达。COX 回归分析表明，构建的纤维化评分模型是甲状腺癌患者的独立预后预测因子（HR = 5.17，95%CI 2.31-11.56，P = 6.36E-05）。在 TCGA 数据集，纤维化评分低的患者总生存期（OS）明显优于纤维化评分高的患者（P = 7.659E-04）。特定免疫细胞浸润水平与纤维化评分呈正相关，包括单核细胞、M1 巨噬细胞和嗜酸性粒细胞。

结论

我们的研究展示了甲状腺癌微环境中成纤维细胞特征的全面概况，这可能为甲状腺癌治疗提供潜在价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43df/9643292/adda0ff4cbf0/fendo-13-1019072-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43df/9643292/6f3ede67151b/fendo-13-1019072-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43df/9643292/adda0ff4cbf0/fendo-13-1019072-g007.jpg

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