State-Aware RNA Biomarkers in Triple-Negative Breast Cancer (TNBC): Integrating Tumor Plasticity, Spatial...

Triple-negative breast cancer is defined by the absence of druggable receptor targets and by a biologically dynamic phenotype that renders static, single-timepoint biomarker strategies fundamentally inadequate. Current predictive markers, including PD-L1 expression, tumor mutational burden, and genomic profiling, fail to capture the therapy-induced transcriptional reprogramming, spatial heterogeneity, and drug-tolerant persister states that drive resistance and relapse. In this review, we argue that RNA, particularly non-coding RNA (ncRNA), represents a complementary and state-aware platform for biomarker development in TNBC, capable of capturing transcriptional adaptation, regulatory threshold dynamics, and cell state transitions that static genomic markers cannot fully detect. Unlike messenger RNAs, which reflect active transcriptional programs, long non-coding RNAs and circular RNAs modulate the stability of state transitions and are specifically induced under conditions of therapeutic stress, immune exclusion, and drug tolerance, which are properties that make them suitable as potential early and sensitive indicators of adaptive reprogramming. We review the biological rationale for RNA as a state-aware readout across five dimensions: tumor plasticity, immune context, stress response, therapy adaptation, and microenvironment composition. An examination is conducted regarding how spatial transcriptomics can map RNA-defined resistant niches within TNBC, how serial liquid biopsy RNA measurements, including extracellular vesicle RNA and circulating tumor RNA, enable temporal monitoring of transcriptional state shifts before radiologic progression, and what analytical and clinical standards deployable RNA assays must meet. Finally, a state-guided adaptive management framework is proposed in which RNA signatures function as iteratively updated measurement layers informing therapy selection, on-treatment monitoring, and early resistance detection. This review outlines trial design models and defines the validation standards required before RNA-guided adaptation can enter clinical practice.