Abstract 3453: Cancer Cell Line Factory: A systematic approach to create next-generation cancer model at scale

Abstract

Precision cancer medicine is based on the ability to predict the dependencies of a given tumor from its molecular makeup. Despite successes in multiple common cancers, such prediction remains challenging for the majority of rare and understudied tumors given the absence of laboratory model systems in which to discover and/or validate therapeutic hypotheses. Here, we describe our efforts to address this challenge systematically with the ultimate goal of making it possible to learn how to predict ex vivo growth requirements for cancer samples based on technical, clinical and genomic properties of the starting tumor material. Over the last 5 years, we have processed nearly 2,000 tumor biospecimens and created over 375 genomically-confirmed patient-derived cell lines, organoids and neurosphere cultures, with >10% of these representing rare cancers. To make this possible, we have implemented three key workflows including (1) direct-to-patient sample sourcing, (2) a tissue cryopreservation and genomic credentialing system to ensure quality prior to model creation, and (3) a systematic empirical approach to screening rich medias and variations on organoid technologies ex vivo (HYBRID). We have begun performing genome-wide CRISPR viability screens in these cultures as part of our larger activities to generate a systematic laboratory-based functional map of cancer dependencies (a ‘Cancer Dependency Map'). The novel organoid, spheroid and cell line models created as part of this effort are being made publically available to the scientific community. Looking ahead, as the barriers to culturing rare tumors are overcome, we expect that preclinical functional genomics data will be useful for difficult-to-treat tumors without existing molecularly guided standard-of-care regimens. Citation Format: Yuen-Yi Tseng, Mushriq AI-Jazrawe, Rebecca Deasy, Paula Keskula, Grace Johnson, Andrew Hong, Priya Chatterji, Francisca Vasquez, Adam Bass, Barbara Van Hare, David Sandak, Keith Ligon, Jesse Boehm. Cancer Cell Line Factory: A systematic approach to create next-generation cancer model at scale [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3453.

TCGADEPMAP– Mapping Translational Dependencies and Synthetic Lethalities within The Cancer Genome Atlas

“…One approach to understanding tumor dependencies is through genomewide genetic and chemical perturbation datasets (e.g., DEPMAP ( 7, 8 ), Project SCORE ( 9 ), and Connectivity Map ( 10 )) that have been paired with thousands of deeply characterized cancer models (e.g., Cancer Cell Line Encyclopedia ( 11 ), Cancer Cell Line Factory, ( 12 ), and Human Cancer Models Initiative ( 13 )). Multiple studies have demonstrated the ability of DEPMAP to translate gene essentially to novel therapeutic targets ( 14 – 18 ) and a broader functional understanding of tumor dependencies ( 19, 20 ).…”