Dormant tumor cells are a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. They are commonly found in multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease following surgical removal of the primary tumor. These cells are closely associated with long-term clinical latency and late-stage relapse. Owing to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that selectively target rapidly dividing cells. In addition, they exhibit enhanced anti-apoptotic capacity and immune evasion, making them particularly difficult to eliminate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This capacity to escape dormancy underscores their clinical threat and positions their effective detection and eradication as a major challenge in current cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and limited the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy is accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, apoptosis resistance, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K–AKT–mTOR, Ras–Raf–MEK–ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been investigated in depth, most studies remain reductionist and fail to capture the temporal progression and network-level coordination that underlie dormancy transitions. Systems biology provides a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks that encompass key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and clarify functional interactions among key effectors. When combined with dynamic modeling approaches, such as ordinary differential equations, these frameworks enable simulation of the temporal behavior of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, shedding light on how their dynamic changes govern state transitions between proliferation and dormancy. Beyond mapping the trajectory from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A have emerged as pivotal nodes in these networks and hold strong potential as therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is therefore essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies that target dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.