Nanomechanical properties of living cells, as measured with atomic force microscopy (AFM), are increasingly recognized as criteria that differentiate normal and pathologically altered cells. Locally measured cell elastic properties, described by the parameter known as Young's modulus, are currently proposed as a new diagnostic parameter that can be used at the early stage of cancer detection. In this study, local mechanical properties of normal human prostate (RWPE-1) cells and a range of malignant (22Rv1) and metastatic prostate cells (LNCaP, Du145 and PC3) were investigated. It was found that non-malignant prostate cells are stiffer than cancer cells while the metastatic cells are much softer than malignant cells from the primary tumor site. Next, the biochemical properties of the cells were measured using confocal Raman (RS) and Fourier-transform infrared (FT-IR) spectroscopies to reveal these cells’ biochemical composition as malignant transformation proceeds. Nanomechanical and biochemical profiles of five different prostate cell lines were subsequently analyzed using partial least squares regression (PLSR) in order to identify which spectral features of the RS and FT-IR spectra correlate with the cell's elastic properties. The PLSR-based model could predict Young's modulus values based on both RS and FT-IR spectral information. These outcomes show not only that AFM, RS and FT-IR techniques can be used for discrimination between normal and cancer cells, but also that a linear correlation between mechanical response and biomolecular composition of the cells that undergo malignant transformation can be found. This knowledge broadens our understanding of how prostate cancer cells evolve thorough the multistep process of tumor pathogenesis.

用原子力显微镜（AFM）测量的活细胞的纳米力学性能已被越来越多地视为区分正常细胞和病理改变细胞的标准。当前提出了由称为杨氏模量的参数描述的局部测量的细胞弹性性质，作为可以在癌症检测的早期阶段使用的新诊断参数。在这项研究中，研究了正常人前列腺（RWPE-1）细胞以及一系列恶性（22Rv1）和转移性前列腺细胞（LNCaP，Du145和PC3）的局部力学性能。发现原发肿瘤部位的非恶性前列腺细胞比癌细胞坚硬，而转移性细胞比恶性细胞软得多。下一个，使用共聚焦拉曼（RS）和傅立叶变换红外（FT-IR）光谱仪测量细胞的生化特性，以揭示随着恶性转化的进行，这些细胞的生化组成。随后使用偏最小二乘回归（PLSR）分析了五种不同前列腺细胞系的纳米力学和生化特征，以鉴定RS和FT-IR光谱的哪些光谱特征与细胞的弹性有关。基于PLSR的模型可以基于RS和FT-IR光谱信息预测杨氏模量值。这些结果不仅表明AFM，RS和FT-IR技术可用于区分正常细胞和癌细胞，而且还可以发现机械反应与经历恶性转化的细胞的生物分子组成之间存在线性相关性。这些知识拓宽了我们对前列腺癌细胞如何在肿瘤发病机理的多步骤过程中进化的理解。