<p>Supplemental Table 3: List of alternatively spliced genes identified in response to SF3B1 mutant</p>

Supplemental Figure 1. Efficient knockâ€in of DDâ€domain into the endogenous p53 locus by TALENs in HCT116 cells. Supplemental Figure 2. PCR verification of Degronâ€KI clones. Supplemental Figure 3. Immunofluorescence staining of Degronâ€KI cells. Supplemental Figure 4. Quantification of DD tagged proteins in the presence or absence of Shld. Supplemental Figure 5. Highly efficient Degronâ€KI at the endogenous EZH2 locus by CRISPR in HCT116. Supplemental Figure 6. Assessment of the kinetics of DDâ€EZH2 and DDâ€SF3B1 depletion upon Shld withdrawal. Supplemental Figure 7. HCT116 (EZH2 wild type) cells are not sensitive to EZH2 inhibitor EI1. Supplemental Figure 8. RTâ€PCR strategy to identify allele†specific DD tagging of mutant versus wildtype SF3B1. Supplemental Figure 9. UQCC and CRNDE exhibit an altered splice pattern in SF3B1 mutant uveal melanoma cell lines. Supplemental Figure 10. Shld has minimal effects on gene expression of parental Mel202 cells and Mel202 DDâ€mutâ€SF3B1. Supplemental Figure 11. Selective depletion of mutant SF3B1 in Mel202 Degronâ€KI cells reversed the alternative splicing pattern of DYNLL1, SNRPN, TMEM14C, ABCC5, ZDHHC16, RBM18. Supplemental Figure 12. Selective depletion of mutant SF3B1 in Mel202 Degronâ€KI cells by Shld withdrawal predominantly alters 3' splice sites but not 5' splice site selection. Supplemental Figure 13. Confirmation that the DD tag insertion occurred exclusively at the SF3B1 locus in Degronâ€KI engineered Mel202 clones. Supplemental Table 1: Detailed genotypes of ESSâ€1 Degronâ€KI clones. Supplemental Table 2: Detailed genotypes of Mel202 Degronâ€KI clones. depletion using MATS. Supplemental Table 4: Comparison of the alternatively spliced genes identified in this study with genes reported in prior reports (5).

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.

Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.

Abstract Recent advances in next-generation sequencing have revealed the presence of genetic heterogeneity and clonal evolution within tumors. Intratumoral heterogeneity has been implicated in the disease progression, metastasis, therapeutic responses and development of drug resistance. Although cancer cell line xenograft models have been extensively used in cancer research to test drug efficacy, it is unknown how much clonal heterogeneity is maintained in the process of cell line xenograft establishment. In order to quantitatively assess the clonal complexity in xenograft models, here we applied a cellular barcoding technology using the HCC827 cell line. HCC827 is a non-small cell lung cancer cell line containing an exon 19 deletion which has been shown to be clinically relevant due to its initial response to EGFR inhibitors followed by resistance. This barcoding tool allowed us to label each individual cell with one unique DNA barcode via lentiviral infection and monitor the clonal heterogeneity within the implanted cell population by quantifying the number of unique barcodes. We were able to estimate the percentage of implanted clones that actually contributed to the formation of cell line xenografts. This study provides valuable insight on the clonal diversity present in xenograft models, which will further elucidate the heterogeneous nature of tumors. Citation Format: Justina X. Caushi, Hyo-eun C. Bhang, Jie Li, Iris Kao, Viveksagar Krishnamurthy Radhakrishna, Vesselina G. Cooke, Joshua M. Korn, David A. Ruddy, Shailaja Kasibhatla, Frank Stegmeier. Understanding clonal complexity of a tumor xenograft model via cellular barcoding technology. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3240. doi:10.1158/1538-7445.AM2015-3240

AbstractAssessing the functional significance of novel putative oncogenes remains a significant challenge given the limitations of current loss-of-function tools. Here, we describe a method that employs TALEN or CRISPR/Cas9-mediated knock-in of inducible degron tags (Degron-KI) that provides a versatile approach for the functional characterization of novel cancer genes and addresses many of the shortcomings of current tools. The Degron-KI system allows for highly specific, inducible, and allele-targeted inhibition of endogenous protein function, and the ability to titrate protein depletion with this system is able to better mimic pharmacologic inhibition compared with RNAi or genetic knockout approaches. The Degron-KI system was able to faithfully recapitulate the effects of pharmacologic EZH2 and PI3Kα inhibitors in cancer cell lines. The application of this system to the study of a poorly understood putative oncogene, SF3B1, provided the first causal link between SF3B1 hotspot mutations and splicing alterations. Surprisingly, we found that SF3B1-mutant cells are not dependent upon the mutated allele for in vitro growth, but instead depend upon the function of the remaining wild-type alleles. Collectively, these results demonstrate the broad utility of the Degron-KI system for the functional characterization of cancer genes. Cancer Res; 75(10); 1949–58. ©2015 AACR.