Genomics has transformed oncology, yet molecular data alone still falls short in predicting patient responses. The next decade requires marrying tumor profiling with systematic, scalable functional testing of patient-derived models to guide therapy, accelerate discovery, and inform precision medicine.
In this talk, Dr. Boehm will first provide an update on a large-scale international program—the Human Cancer Models Initiative (HCMI) - which consented more than 2,500 donors resulting in the production and subsequent characterization of 665 organoid, neurosphere and cell line models by whole genome, exome, methylome, and transcriptome analysis. Analysis of 421 matched tumor/model pairs revealed a high degree of genetic (97.8%) and epigenetic (95%) concordance and defined specific correlates of discordance and model fidelity. However, single-nucleus RNA sequencing shows that, for some models, detectable cell states are influenced by culture conditions. This new internationally accessible community resource provides a roadmap for capturing an increasing spectrum of cancer diversity in preclinical models, extending previous initiatives substantially.
He will also provide an update on the development of new technologies to validate therapeutic hypotheses at immediate-early ex vivo timepoints in which cellular heterogeneity is maintained. Specifically, Dr. Boehm will describe the initial development of AscitesPredict, an ‘ex vivo tumor biosensor’ technology using single cell technologies to measure cell identities and therapeutic sensitivities of solid tumor ascites fluid during a 5 day ex vivo period in which viability is preserved. AscitesPredict utilizes high dimensional single cell image-based morphological profiling and machine learning applied to brightfield microscopy to profile both cancer and immune cells and subpopulations. Thus far, we have profiled over 50 GEA ascites samples, made initial assessments of technological reproducibility, and have optimized initial workflows. Our ultimate goal is to harden this precision functional genomics technology to facilitate deployment by a wide diversity of researchers and clinicians for two driving use cases: (1) supporting preclinical drug development and (2) eventually as a functional diagnostic.