Ji Mingyu, Fan Daming, Yuan Yaqi, Wang Jing, Feng Xiaodong, Yang Weihua, Dang Xiaofei, Xu Yihui, Wang Jun
Medical Research and Laboratory Diagnostic Center, Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Department of Pathology, Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Cancer Biother Radiopharm. 2025 Apr 30. doi: 10.1089/cbr.2025.0043.
Lung combined large-cell neuroendocrine carcinoma (CoLCNEC) refers to lung regions exhibiting both the features of large-cell neuroendocrine carcinoma (LCNEC) and the defined components of nonsmall cell lung cancer (NSCLC), with a relatively high mitotic rate. Diagnosing and predicting the prognosis of CoLCNEC are challenging. This study aimed to explore spatial transcriptomic expression patterns and identify crucial genes. We utilized a sample from a CoLCNEC patient containing three distinct components, namely, LCNEC, adenocarcinoma, and squamous cell carcinoma, with the former being predominant. Spatial transcriptomics (ST) technology, which employs the 10× Genomics Visium formalin-fixed paraffin-embedded ST kit, was applied along with high-throughput sequencing to obtain gene expression information and spatial locations for each spot. Subsequent analysis included differentially gene expression and functional enrichment. Finally, immunohistochemistry was employed to validate the marker protein structural maintenance of chromosomes 1A (). Then, was overexpressed and silenced in NCI-H661 and LTEP-a-2 cells, and the migration and invasion ability of the cells were detected by scratch assay and Transwell, respectively. The role of in cancer cell cycle was detected by Real-time Reverse Transcription-PCR(RT-qPCR), Western blot, and flow cytometry, the apoptosis was detected by flow cytometry. The results revealed that tumor tissue regions had higher unique molecular identifiers and gene counts than nontumor regions did. Unsupervised clustering identified four clusters, revealing the uniform distribution of unique transcripts, which were mapped onto slices to display apparent spatial separation. Differentially gene expression analysis revealed genes highly expressed in cancer cells. Further analysis of different regions revealed distinct cellular subgroups enriched through differentially gene expression analysis in various pathways, such as the cell cycle and DNA replication. Finally, was chosen as a candidate gene, and immunohistochemistry confirmed its elevated expression in tumor regions. In addition, compared with oe-NC, oe- can significantly promote the migration, invasion and G1/S phase transition of lung cancer cells, and promote the inhibition of apoptosis of cancer cells, while sh- is completely opposite. In the tumor region of CoLCNEC, is significantly upregulated. Moreover, silencing effectively inhibits lung cancer cell invasion, migration, and G1/S phase transition, while promoting apoptosis. These findings indicate that has the potential to be a new therapeutic target for CoLCNEC treatment.
肺复合型大细胞神经内分泌癌（CoLCNEC）是指肺部区域同时呈现大细胞神经内分泌癌（LCNEC）特征和非小细胞肺癌（NSCLC）特定成分，且有相对较高的有丝分裂率。CoLCNEC的诊断和预后预测具有挑战性。本研究旨在探索空间转录组表达模式并鉴定关键基因。我们使用了一名CoLCNEC患者的样本，该样本包含三个不同成分，即LCNEC、腺癌和鳞状细胞癌，其中LCNEC占主导。采用10×Genomics Visium福尔马林固定石蜡包埋空间转录组（ST）试剂盒的空间转录组学（ST）技术，并结合高通量测序，以获取每个斑点的基因表达信息和空间位置。后续分析包括差异基因表达和功能富集。最后，采用免疫组织化学法验证染色体结构维持蛋白1A（）的标记蛋白。然后，在NCI-H661和LTEP-a-2细胞中过表达和沉默，分别通过划痕试验和Transwell检测细胞的迁移和侵袭能力。通过实时逆转录聚合酶链反应（RT-qPCR）、蛋白质免疫印迹法和流式细胞术检测在癌细胞周期中的作用，通过流式细胞术检测细胞凋亡。结果显示，肿瘤组织区域比非肿瘤区域具有更高的独特分子标识符和基因计数。无监督聚类识别出四个簇，揭示了独特转录本的均匀分布，这些转录本被映射到切片上以显示明显的空间分离。差异基因表达分析揭示了癌细胞中高表达的基因。对不同区域的进一步分析揭示了通过差异基因表达分析在各种途径（如细胞周期和DNA复制）中富集的不同细胞亚群。最后，选择作为候选基因，免疫组织化学证实其在肿瘤区域表达升高。此外，与oe-NC相比，oe-可显著促进肺癌细胞的迁移、侵袭和G1/S期转变，并促进癌细胞凋亡的抑制，而sh-则完全相反。在CoLCNEC的肿瘤区域，显著上调。此外，沉默可有效抑制肺癌细胞的侵袭、迁移和G1/S期转变，同时促进细胞凋亡。这些发现表明，有潜力成为CoLCNEC治疗的新靶点。
