progression. Expanding upon this idea, in chapter 2, we report a systematic and comprehensive search to identify, annotate, and characterize cancer-emergent oncRNAs across 32 tumor types. We leverage large-scale in vivo genetic screens in xenografted mice to functionally identify driver oncRNAs in multiple tumor types. We not only discover a large repertoire of oncRNAs, but also find that their presence and absence represent a digital molecular barcode that faithfully captures the types and subtypes of cancer. Importantly, we discover that this molecular barcode is partially accessible from the cell-free space as some oncRNAs are secreted by cancer cells. In a large retrospective study across 192 breast cancer patients, we show that oncRNAs can be reliably detected in the blood and that changes in the cell-free oncRNA burden captures both short-term and long-term clinical outcomes upon completion of a neoadjuvant chemotherapy regimen. Together, our findings establish oncRNAs as an emergent class of cancer-specific non-coding RNAs with potential roles in tumor progression and clinical utility in liquid biopsies, providing the first tumor-naive minimum residual disease monitoring approach for breast cancer.Lastly, we explore the utilization of intrinsic transcriptional noise encoded within the cell as a mechanism of tumor proliferation and resistance in the face of unfamiliar microenvironments. More specifically, intratumoral heterogeneity (ITH) is recognized as a driver of therapeutic resistance and fatal cancer recurrence. ITH occurs at both a genetic and transcriptional level and enables tumor cells to adapt to variable environmental pressures, such as hypoxia, immune surveillance, and targeted molecular therapy. In chapter 3, through integrating in silico analysis of BRCA TCGA-RNA-Seq data, in vivo CRISPRi screens, and in vitro single-cell transcriptomics, we identify RNF8 and MIS18A as drivers of transcriptional heterogeneity. Modulating expression of these two genes impacts cellular fitness, chemotherapeutic sensitivity, and metastatic potential in a proportional manner, underscoring their roles in driving cancer progression. Analysis of human breast cancer patient data reveals that increased expression of