Personalized medicine, enabling each patient to receive earlier diagnoses, risk assessments, and optimal treatments hold promise for improving cancer health care while also lowering costs. For example, more than 60% of breast cancers (BC) in women are diagnosed as estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-), which is then typically treated with adjuvant therapy that combines endocrine therapy with CDK4/6 inhibitors (CDK4/6i). In addition to high cost, CDK4/6i treatment time can increase particularly within the <50% patient population that experiences drug resistance and who must proceed to a second line of treatment. Exosomes are membrane-bound extracellular vesicles that have recently demonstrated rapid growth in BC research due to their vast array of tissue-specific surface markers and molecular contents that can be used to confirm a prognosis. For example, overexpression of exosomal TK1 is associated with CDK4/6i resistance; thus, exosomal cargo content can be analyzed to enable tailored treatment with the best response and highest safety margin for ER+/HER2- BC patients. However, exosome heterogeneity has hindered research progress due to lagging analytical techniques to effectively characterize and isolate BC-specific exosomes. This project combines an oligonucleotide hybridization reaction with temperature-sensitive polymer-oligonucleotide conjugates that can detect and rapidly isolate specific exosome subtypes depending on tissue-specific exosome surface proteins. We expect that the isolated exosome cargo will quantitatively demonstrate susceptibility or building resistance to CDK4/6i. Future work includes optimizing the oligonucleotide sequence, further pinpointing target BC-specific surface markers, testing the assay, and comparing results to current methodologies. Ultimately, enabling an exosome liquid biopsy method to tailor patient-specific BC treatments can decrease the overall time, cost, and toxicity associated with current non-specific cancer treatment methods and can also be utilized in monitoring dynamic cancer metastasis.