研究新陈代谢可能有助于了解正常和功能失调的线粒体活动与各种疾病（如神经退行性疾病、心血管疾病、自身免疫性疾病、精神病和癌症）之间的关系。基于核磁共振的代谢组学代表了一种表征复杂样品化学含量的强大方法，并已成功应用于研究一系列条件。然而，缺乏分析分离的细胞器（例如线粒体）的优化方法。在这项研究中，我们报告了一种对健康组织、肿瘤组织和转移组织的线粒体进行代谢分析的方案的开发。令人鼓舞的是，这种方法在一项全面而稳健的分析中提供了多达 45 种代谢物的定量信息。我们的结果揭示了全细胞和线粒体代谢物之间的显着差异，这支持了更精细的代谢分析方法。我们应用优化的方法来研究小鼠组织中的侵袭性和转移性乳腺癌，发现肺线粒体表现出改变的代谢指纹。与健康组织的线粒体相比，特定氨基酸、有机酸和脂质的水平显着增加。我们优化的方法可以促进更好地理解乳腺癌侵袭性和线粒体相关疾病的分子机制，并支持新的先进疗法的优化。

Studying metabolism may assist in understanding the relationship between normal and dysfunctional mitochondrial activity and various diseases, such as neurodegenerative, cardiovascular, autoimmune, psychiatric, and cancer. Nuclear magnetic resonance-based metabolomics represents a powerful method to characterize the chemical content of complex samples and has been successfully applied to studying a range of conditions. However, an optimized methodology is lacking for analyzing isolated organelles, such as mitochondria. In this study, we report the development of a protocol to metabolically profile mitochondria from healthy, tumoral, and metastatic tissues. Encouragingly, this approach provided quantitative information about up to 45 metabolites in one comprehensive and robust analysis. Our results revealed significant differences between whole-cell and mitochondrial metabolites, which supports a more refined approach to metabolic analysis. We applied our optimized methodology to investigate aggressive and metastatic breast cancer in mouse tissues, discovering that lung mitochondria exhibit an altered metabolic fingerprint. Specific amino acids, organic acids, and lipids showed significant increases in levels when compared with mitochondria from healthy tissues. Our optimized methodology could promote a better understanding of the molecular mechanisms underlying breast cancer aggressiveness and mitochondrial-related diseases and support the optimization of new advanced therapies.