<p>Targeted cancer therapy is often compromised by the development of acquired drug resistance. Beyond genetic mutations, recent studies underscore the role of non-genetic plasticity and adaptive network rewiring in driving this resistance. Overcoming this challenge requires innovative approaches, including the integration of transcriptomics and natural product research. Natural products are chemically diverse agents that can modulate multiple resistance pathways due to their polypharmacological properties. In parallel, transcriptomic profiling of drug-exposed cells provides genome-wide snapshots of resistance states and reveals how candidate compounds remodel these cells. This review summarizes the methods by which transcriptomics facilitates the identification of natural products that overcome resistance to targeted therapies. It outlines the canonical resistance mechanisms and highlights the natural products that reverse these adaptive networks at the molecular level. It then discusses how systematic transcriptomic workflows, including differential expression profiling, pathway analysis, and perturbome matching, elucidate the modes of action of natural compounds. This data-driven framework facilitates the discovery of novel agents, supports drug repurposing, and guides the rational design of combination therapies to restore drug sensitivity. Finally, it addresses clinical translation barriers and emerging computational frontiers, such as multi-omics and artificial intelligence, which will increasingly play vital roles in harnessing the therapeutic potential of natural products in patients with resistant cancers.</p>