Proietto Marco, Crippa Martina, Damiani Chiara, Pasquale Valentina, Sacco Elena, Vanoni Marco, Gilardi Mara
Next Generation Sequencing Core, The Salk Institute for Biological Studies, La Jolla, CA, United States.
Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States.
Front Oncol. 2023 Apr 28;13:1164535. doi: 10.3389/fonc.2023.1164535. eCollection 2023.
Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.
肿瘤异质性描述了肿瘤内部和肿瘤之间癌细胞的差异。它指的是癌细胞在形态、转录谱、代谢和转移潜能方面存在的差异。最近，该领域还包括肿瘤免疫微环境的特征描述以及对促进肿瘤生态系统进化的细胞间相互作用潜在动态变化的描绘。在大多数肿瘤中都发现了异质性，这是癌症生态系统中最具挑战性的行为之一。作为损害实体瘤治疗长期疗效的关键因素之一，异质性会导致肿瘤耐药、更具侵袭性的转移和复发。我们综述了主要模型以及新兴的单细胞和空间基因组技术在我们理解肿瘤异质性、其对致命性癌症结局的影响以及设计癌症治疗方案时需要考虑的生理挑战方面所发挥的作用。我们强调肿瘤细胞如何因肿瘤免疫微环境中的相互作用而动态进化，以及如何利用这一点通过免疫疗法释放免疫识别作用。基于新型生物信息学和计算工具的多学科方法将有助于实现对肿瘤异质性的综合、多层次认识，这是实施癌症患者迫切需要的个性化、更有效治疗所必需的。
