DataSheet_1_The expression characteristics of transmembrane protein genes in pancreatic ductal adenocarcinoma through comprehensive analysis of bulk and single-cell RNA sequence.pdf

BackgroundTransmembrane (TMEM) protein genes are a class of proteins that spans membranes and function to many physiological processes. However, there is very little known about TMEM gene expression, especially in cancer tissue. Using single-cell and bulk RNA sequence may facilitate the understanding of this poorly characterized protein genes in PDAC.
MethodsWe selected the TMEM family genes through the Human Protein Atlas and characterized their expression by single-cell and bulk transcriptomic datasets. Identification of the key TMEM genes was performed through three machine learning algorithms: LASSO, SVM-RFE and RF-SRC. Then, we established TMEM gene riskscore and estimate its implication in predicting survival and response to systematic therapy. Additionally, we explored the difference and impact of TMEM gene expression in PDAC through immunohistochemistry and cell line research.
Results5 key TMEM genes (ANO1, TMEM59, TMEM204, TMEM205, TMEM92) were selected based on the single-cell analysis and machine learning survival outcomes. Patients stratified into the high and low-risk groups based on TMEM riskscore, were observed with distinct overall survival in internal and external datasets. Moreover, through bulk RNA-sequence and immunohistochemical staining we verified the protein expression of TMEM genes in PDAC and revealed TMEM92 as an essential regulator of pancreatic cancer cell proliferation, migration, and invasion.
ConclusionOur study on TMEM gene expression and behavior in PDAC has revealed unique characteristics, offering potential for precise therapeutic approaches. Insights into molecular mechanisms expand understanding of PDAC complexity and TMEM gene roles. Such knowledge may inform targeted therapy development, benefiting patients.

背景：跨膜蛋白（Transmembrane, TMEM）编码基因是一类具备跨膜结构、参与众多生理过程的蛋白质家族。然而目前学界对TMEM基因的表达模式，尤其是在癌组织中的表达特征仍知之甚少。借助单细胞RNA测序与批量RNA测序技术，或可帮助我们深入理解胰腺导管腺癌（Pancreatic Ductal Adenocarcinoma, PDAC）中这类特征尚未明确的蛋白编码基因。

研究方法：本研究通过人类蛋白质图谱（Human Protein Atlas）筛选得到TMEM家族基因，并借助单细胞与批量转录组数据集对其表达特征进行系统解析。通过三种机器学习算法——最小绝对收缩与选择算子（Least Absolute Shrinkage and Selection Operator, LASSO）、支持向量机-递归特征消除（Support Vector Machine-Recursive Feature Elimination, SVM-RFE）以及随机森林-生存递归特征消除（Random Forest-Survival Recursive Feature Elimination, RF-SRC）——完成关键TMEM基因的筛选与鉴定。随后构建TMEM基因风险评分模型，并评估其在预测患者生存结局与系统治疗响应方面的应用价值。此外，本研究还通过免疫组化实验与细胞系实验，探究了TMEM基因在PDAC中的表达差异及其生物学功能影响。

研究结果：本研究基于单细胞分析与机器学习生存预测结果，筛选得到5个关键TMEM基因：ANO1、TMEM59、TMEM204、TMEM205与TMEM92。根据TMEM基因风险评分将患者划分为高风险组与低风险组后，在内部与外部验证数据集中均可观察到两组患者的总生存期存在显著差异。此外，通过批量RNA测序与免疫组化染色实验，本研究验证了TMEM基因在PDAC组织中的蛋白表达水平，并证实TMEM92是胰腺癌细胞增殖、迁移与侵袭的关键调控因子。

研究结论：本研究针对PDAC中TMEM基因的表达模式与生物学行为展开系统分析，揭示了该家族基因的独特临床与生物学特征，为精准治疗策略的开发提供了潜在方向。对相关分子机制的深入解析，进一步增进了学界对PDAC复杂性以及TMEM基因功能的认知。上述研究成果可为靶向治疗药物的开发提供理论依据，最终惠及胰腺导管腺癌患者。