Table 3_Unveiling the NEFH+ malignant cell subtype: Insights from single-cell RNA sequencing in prostate cancer progression and tumor microenvironment interactions.xlsx

BackgroundProstate cancer (PCa) is a multifactorial and heterogeneous disease, ranking among the most prevalent malignancies in men. In 2020, there were 1,414,259 new cases of PCa worldwide, accounting for 7.3% of all malignant tumors. The incidence rate of PCa ranks third, following breast cancer and lung cancer. Patients diagnosed with high-grade PCa frequently present with existing or developing metastases, complicating their treatment and resulting in poorer prognoses, particularly for those with bone metastases. Utilizing single-cell RNA sequencing (scRNA-seq), we identified specific malignant cell subtypes that are closely linked to high-grade PCa. By investigating the mechanisms that govern interactions within the tumor microenvironment (TME), we aim to offer new theoretical insights that can enhance the prevention, diagnosis, and treatment of PCa, ultimately striving to improve patient outcomes and quality of life.
MethodsData on scRNA-seq was obtained from the GEO database. The gene ontology and gene set enrichment analysis were employed to analyze differential expression genes. Using inferCNV analysis to identify malignant epithelial cells. We subsequently employed Monocle, Cytotrace, and Slingshot packages to infer subtype differentiation trajectories. The cellular communication between malignant cell subtypes and other cells was predicted using the CellChat package. Furthermore, we employed pySCENIC to analyze and identify the regulatory networks of transcription factors (TFs) in malignant cell subtypes. The MDA PCa 2b and VCap cell lines were employed to validate the analysis results through cellular functional experiments. In addition, a risk scoring model was developed to assess the variation in clinical characteristics, prognosis, immune infiltration, immune checkpoint, and drug sensitivity.
ResultsA malignant cell subtype in PCa with high expression of NEFH was identified through scRNA-seq analysis. This subtype was situated at the differentiation terminal, exhibited a higher level of malignancy, and exhibited characteristics that were more prone to advanced tumor lesions. In addition, our research underscored the intricate interactions that exist within the TME, particularly the interaction between PTN secreted by this subtype and fibroblasts via the NCL receptor. This interaction may be closely associated with cancer-associated fibroblasts and tumor progression. Subsequently, we determined that the NEFH+ malignant cell subtype was significantly correlated with the TF IRX4. This TF is linked to a worse prognosis in PCa and may affect disease progression by regulating gene transcription. Our conclusions were additionally verified through cellular experiments. Furthermore, the prognostic model we developed demonstrated satisfactory predictive performance, with gene sets from the high NmRS group facilitating tumor progression and deterioration. The analysis of immune infiltration was instrumental in the development of clinical intervention strategies and patient prognosis.
ConclusionBy examining the cellular heterogeneity of a unique NEFH+ malignant cell subtype within the PCa microenvironment, we were able to disclose their reciprocal interaction with disease progression. This offers a novel viewpoint on the diagnosis and treatment of PCa.

背景
前列腺癌（Prostate cancer, PCa）是一种多因素、异质性疾病，位列男性最常见的恶性肿瘤之一。2020年，全球新增前列腺癌病例1414259例，占全球恶性肿瘤总发病例数的7.3%，其发病率仅次于乳腺癌与肺癌，位居男性恶性肿瘤第三位。确诊高级别前列腺癌的患者常已存在或进展出现转移灶，这会增加治疗难度并导致更差的预后，伴骨转移患者的预后尤甚。本研究借助单细胞RNA测序（single-cell RNA sequencing, scRNA-seq），鉴定出与高级别前列腺癌密切相关的特定恶性细胞亚型。通过探究调控肿瘤微环境（tumor microenvironment, TME）内细胞互作的机制，本研究旨在为前列腺癌的预防、诊断与治疗提供新的理论见解，最终以期改善患者的转归与生活质量。
方法
本研究的单细胞RNA测序数据来源于基因表达综合数据库（Gene Expression Omnibus, GEO）。采用基因本体（Gene Ontology, GO）富集分析与基因集富集分析（Gene Set Enrichment Analysis, GSEA）对差异表达基因进行分析；通过inferCNV分析鉴定恶性上皮细胞。随后借助Monocle、Cytotrace及Slingshot工具包推断各细胞亚型的分化轨迹；利用CellChat工具包预测恶性细胞亚型与其他细胞间的细胞通讯。此外，采用pySCENIC分析并鉴定恶性细胞亚型中转录因子（transcription factors, TFs）的调控网络。本研究选用MDA PCa 2b与VCap细胞系，通过细胞功能实验对分析结果进行验证。此外，本研究构建了风险评分模型，用以评估临床特征、预后、免疫浸润、免疫检查点及药物敏感性的差异。
结果
通过单细胞RNA测序分析，本研究鉴定出一种高表达NEFH的前列腺癌恶性细胞亚型。该亚型处于细胞分化终末阶段，恶性程度更高，且更易进展为晚期肿瘤病变。此外，本研究揭示了肿瘤微环境内复杂的细胞互作网络，尤其是该亚型分泌的PTN通过NCL受体与成纤维细胞的相互作用，这一互作过程可能与癌症相关成纤维细胞及肿瘤进展密切相关。随后，本研究证实NEFH+恶性细胞亚型与转录因子IRX4显著相关，该转录因子与前列腺癌不良预后相关，可通过调控基因转录影响疾病进展。上述研究结论已通过细胞实验得到验证。此外，本研究构建的预后模型展现出良好的预测性能，高NmRS组的基因集可促进肿瘤进展与恶化。免疫浸润分析可为临床干预策略的制定及患者预后评估提供重要参考。
结论
本研究通过解析前列腺癌微环境中独特的NEFH+恶性细胞亚型的细胞异质性，揭示了其与疾病进展的相互作用关系，为前列腺癌的诊断与治疗提供了全新的视角。