Public Health Research Institute (PHRI), Newark, NJ 07103, USA.
Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Rutgers the State University of NJ, Newark, NJ 07103, USA.
Int J Mol Sci. 2018 Apr 24;19(5):1270. doi: 10.3390/ijms19051270.
Neoplastic growth and cellular differentiation are critical hallmarks of tumor development. It is well established that cell-to-cell communication between tumor cells and "normal" surrounding cells regulates tumor differentiation and proliferation, aggressiveness, and resistance to treatment. Nevertheless, the mechanisms that result in tumor growth and spread as well as the adaptation of healthy surrounding cells to the tumor environment are poorly understood. A major component of these communication systems is composed of connexin (Cx)-containing channels including gap junctions (GJs), tunneling nanotubes (TNTs), and hemichannels (HCs). There are hundreds of reports about the role of Cx-containing channels in the pathogenesis of cancer, and most of them demonstrate a downregulation of these proteins. Nonetheless, new data demonstrate that a localized communication via Cx-containing GJs, HCs, and TNTs plays a key role in tumor growth, differentiation, and resistance to therapies. Moreover, the type and downstream effects of signals communicated between the different populations of tumor cells are still unknown. However, new approaches such as artificial intelligence (AI) and machine learning (ML) could provide new insights into these signals communicated between connected cells. We propose that the identification and characterization of these new communication systems and their associated signaling could provide new targets to prevent or reduce the devastating consequences of cancer.
肿瘤细胞的异常生长和细胞分化。目前已经明确，肿瘤细胞与“正常”周围细胞之间的细胞间通讯调节着肿瘤的分化和增殖、侵袭性以及对治疗的耐药性。然而，导致肿瘤生长和扩散的机制以及健康周围细胞对肿瘤微环境的适应机制仍知之甚少。这些通讯系统的一个主要组成部分是包含连接蛋白（Cx）的通道，包括缝隙连接（GJ）、隧道纳米管（TNT）和半通道（HC）。有数百篇关于 Cx 通道在癌症发病机制中的作用的报道，其中大多数表明这些蛋白表达下调。然而，新的数据表明，通过包含 Cx 的 GJ、HC 和 TNT 的局部通讯在肿瘤生长、分化和对治疗的耐药性中发挥着关键作用。此外，不同肿瘤细胞群体之间传递的信号的类型和下游效应仍不清楚。然而，人工智能（AI）和机器学习（ML）等新方法可以为这些连接细胞之间传递的信号提供新的见解。我们提出，鉴定和描述这些新的通讯系统及其相关信号转导可能为预防或减少癌症的毁灭性后果提供新的靶点。
