Single cell RNA-seq and bulk RNA-seq analysis identifies MUC1 as a key gene for lung adenocarcinoma to neuroendocrine transformation.

IF 4 2区 医学 Q2 ONCOLOGY
Translational lung cancer research Pub Date : 2025-03-31 Epub Date: 2025-03-27 DOI:10.21037/tlcr-24-806
Hongxia Li, Tiantian Yang, Yu Chen, Zhiqin Xie
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引用次数: 0

Abstract

Background: Tyrosine kinase inhibitors (TKIs) have demonstrated significant effectiveness in treating advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations. Despite initial success, resistance to EGFR-TKIs inevitably occurs. One observed phenomenon in resistant lung cancers is the histological transformation from NSCLC to neuroendocrine carcinoma (NEC). The objective of this study is to explore and delineate the genetic and immune features linked to the transition from lung adenocarcinoma (LUAD) to NEC.

Methods: Bulk RNA-sequencing and Mendelian randomization (MR) analysis were utilized to identify candidate genes associated with the progression from LUAD to NEC. Expression quantitative trait locus data from publicly available databases were leveraged to pinpoint key genes in relevant tissues. Furthermore, the immune microenvironment was explored using weighted gene co-expression network analysis (WGCNA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) databases. Single-cell RNA sequencing data from 16,765 cells across six tissue biopsy samples of LUAD and NEC were scrutinized to investigate cell interaction networks during histological transformation. The molecular pathways involved in dynamic cellular processes were elucidated through the analysis of cellular communication and pseudotime trajectory.

Results: Through the use of RNA-sequencing and MR analysis, it was determined that mucin-1 (MUC1) displayed a negative correlation with the progression of LUAD to NEC, as evidenced by its downregulation in clinical specimens. Additionally, MUC1 expression was found to be significantly correlated with the infiltration of diverse immune cell populations, notably CD8+ T cells. These results suggest a notable enrichment of neuron-related signaling pathways in the context of transformed NEC. Examination of immune cell infiltration in NEC indicated a reduction in the proportion of CD8+ central memory T cells, which has implications for the immune microenvironment and may point to potential therapeutic targets. Further investigation into cell-cell interactions among subpopulations identified the MIF-CD74 axis as the principal signaling pathway facilitating intercellular communication between immune cells and epithelial cells.

Conclusions: In conclusion, our study provides insights into the molecular landscape governing the LUAD-to-NEC transition, highlighting MUC1 as a potential biomarker. The immune microenvironment is believed to exert a substantial influence on histological transformation, particularly with regards to T cells.

单细胞RNA-seq和整体RNA-seq分析发现MUC1是肺腺癌向神经内分泌转化的关键基因。
背景:酪氨酸激酶抑制剂(TKIs)在治疗表皮生长因子受体(EGFR)突变的晚期非小细胞肺癌(NSCLC)中显示出显著的疗效。尽管最初取得了成功,但对EGFR-TKIs的耐药性不可避免地会发生。在耐药肺癌中观察到的一个现象是从非小细胞肺癌到神经内分泌癌(NEC)的组织学转变。本研究的目的是探索和描述与肺腺癌(LUAD)向NEC过渡相关的遗传和免疫特征。方法:采用大量rna测序和孟德尔随机化(MR)分析来鉴定与LUAD向NEC进展相关的候选基因。利用来自公开数据库的表达数量性状位点数据来确定相关组织中的关键基因。此外,利用加权基因共表达网络分析(WGCNA)和通过估计RNA转录物的相对子集(CIBERSORT)数据库进行细胞类型鉴定来探索免疫微环境。研究人员仔细检查了LUAD和NEC 6个组织活检样本中16,765个细胞的单细胞RNA测序数据,以研究组织学转化过程中的细胞相互作用网络。通过对细胞通讯和伪时间轨迹的分析,阐明了参与细胞动态过程的分子途径。结果:通过rna测序和MR分析,确定mucin-1 (MUC1)与LUAD向NEC的进展呈负相关,在临床标本中mucin-1表达下调。此外,MUC1的表达与多种免疫细胞群的浸润显著相关,尤其是CD8+ T细胞。这些结果表明,在转化NEC的背景下,神经元相关信号通路的显著富集。NEC免疫细胞浸润检查显示CD8+中枢记忆T细胞比例降低,这与免疫微环境有关,可能指向潜在的治疗靶点。对亚群间细胞间相互作用的进一步研究发现,MIF-CD74轴是促进免疫细胞和上皮细胞间细胞间通讯的主要信号通路。结论:总之,我们的研究提供了控制luad到nec转变的分子景观的见解,突出了MUC1作为潜在的生物标志物。免疫微环境被认为对组织学转化,特别是对T细胞产生重大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
2.50%
发文量
137
期刊介绍: Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.
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