This application is submitted in response to Notice of Special Interest (NOSI) NOT-CA-21-009 as an Administrative Supplement to K07 CA230150-03. The goal of Dr. Heidi Hanson’s NCI K07 award is to launch an independent cancer research program focused on improving precision strategies of cancer screening and treatment by integrating genetic, genomic and environmental factors. Pertinent to this Supplement are Research Aim 1: Methodological development of novel multi-omic methods, and Career Development Aim 3: Develop hands-on training in genomic and epigenetic profiling of tumor samples. Currently, her K07 allows her to develop a unique set of skills to improve modeling with transcriptomics in epidemiology. This Supplement would afford her the opportunity to enhance those skills to include translation of the same methods toward clinical interventions. Specifically, it will enhance her career development to include hands-on experience translating her transcriptome methods to the field of pre-clinical models. Her new transcriptome SPECTRA method will concurrently provide potential to advance patient derived xenograph organoid (PDxO) prediction modeling and biomarker development. The project and experience gained will significantly expand the research horizons offered by her NCI K07 and the results gained will be directly relevant to the goals of PDXNet. SPECTRA is novel transcriptome approach to characterize tissue expression using multiple, independent, quantitative variables, or spectra. Dr. Hanson developed the strategy as part of her K07 hands-on training with Dr. Camp. Spectra variables provide a deep dive into complex transcriptome data and show great promise in epidemiology applications. As a novel omic approach, the strategy has excellent potential to enhance incorporation of transcriptome data in other fields, too. In this Supplement, we will: 1) Establish transcriptome spectra for breast tumors using TCGA RNA sequencing data; 2) Apply these quantitative variables to the PDXNet tumors at the Welm lab; and 3) Utilize the spectra variables to build prediction models, classifiers and biomarkers for drug response in PDxO and successful PDX engraftment (an indicator for tumor aggressiveness). New prediction models will uncover drugs and biomarkers for confirmation in vivo in PDX models. Biomarkers provide for patient identification for new clinical trials. Integration of the SPECTRA strategy into preclinical modeling has the potential to provide a new bridge to translate successful drug response findings into prospective clinical trials: a major unmet need and of great interest to PDXNet and NCI.