Supplementary Note 1:

• S1 Text: Oncogenomic comparisons between SB candidate Trunk driver genes and their direct orthologs in human Cancer Gene Census; Pyrosequencing analysis of SB-driven keratinocyte cancer models; References.

Supplementary Figures 1-11:

• S1 Fig: Overview of genetic crosses to generate SB|Trp53|Onc3 mouse model.
• S2 Fig: SB insertion patterns in activated and inactivated drivers.
• S3 Fig: Evaluating the reproducibility of SBCapSeq results from bulk cuSCC and normal skin specimens.
• S4 Fig. Hierarchical two-dimensional clustering of recurrent events in cuKA and cuSCC.
• S5 Fig. Curated biological pathways and processes enriched within SB-induced cuSCC.
• S7 Fig: ZMIZ1 metagene within the TCGA Head & Neck Squamous Cell Carcinoma (hnSCC) RNA-seq dataset.
• S8 Fig: Clonally selected SB insertions affect trunk driver proto-oncogene expression in SB-cuSCC genomes.
• S9 Fig: Clonally selected SB insertions affect trunk driver genes by inactivating expression in SB-cuSCC genomes.
• S10 Fig: CREBBP knockdown does not alter proliferation rate in cuSCC cell lines.
• S11 Fig: Gross photographs of cuSCC xenograft masses collected at necropsy showing robust TurboGFP expression.
• S12 Fig: SB T2/Onc3 TG.12740 allele donor position mapping and exclusion for SB Driver Analysis.

Supplementary Tables 1-20:

• S1 Table: Tumor incidence and subgroup classifications by cohort.
• S2 Table: Specimen metafile data for projects sequenced using SBCapSeq protocol with Ion Torrent Proton sequencer.
• S3 Table: Discovery and progression SB Driver Analysis for cuSCC60_SBC.
• S4 Table: Trunk SB Driver Analysis for cuSCC60_SBC.
• S5 Table: Discovery and progression SB Driver Analysis for cuKA11_SBC.
• S6 Table: Trunk SB Driver Analysis for cuKA11_SBC.
• S7 Table: Discovery and progression SB Driver Analysis for cuSK32_SBC.
• S8 Table: SBCapSeq read depth and analysis for 4 cuSCC genomes selected for multi-region resequencing because they had intermixing of cuSCC and cuKA histologies.
• S9 Table: Enrichr gene set pathway enrichment analysis of cuSCC drivers.
• S10 Table: Summary of 7 cuSCC transcriptomes selected for whole transcriptome RNAseq analysis.
• S11 Table: BED file of SBfusion insertions in 7 cuSCC genomes by whole transcriptome RNAseq analysis.
• S12 Table: Venn diagram for overlap of genes with SBfusion reads detected by whole transcriptome RNAseq analysis and cuSCC60_SBC discovery driver.
• S13 Table: Venn diagram for overlap of genes with SBfusion reads detected by whole transcriptome RNAseq analysis and all cuSCC drivers.
• S14 Table: Transcripts per million (TPM) normalized whole transcriptome RNAseq values per gene from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.
• S15 Table: Fragments Per Kilobase of Transcripts per Million (FPKM) normalized whole transcriptome RNAseq values per gene transcript from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.
• S16 Table: Normalized microarray values per gene from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.
• S17 Table: Normalized microarray values per probe from RNA isolated from cuSCC genomes with and without Zmiz1 insertions.
• S18 Table: All 289 genes with differential expression analysis from microarray data from RNA isolated from cuSCC genomes with and without Zmiz1 insertions with P<0.0001 and q<0.05.
• S19 Table: Lentiviral vectors containing shRNAs used in this study.
• S20 Table: TaqMan probes used in this study.

Supplementary Datasets 1-5:

• S1 Data: BED file of SB insertions for cuSCC60_SBC.
• S2 Data: BED file of SB insertions for cuKA11_SBC.
• S3 Data: BED file of SB insertions for cuSK32_SBC
• S4 Data: BED file of SB insertions for 4 cuSCC genomes selected for multi-region resequencing because they had intermixing of cuSCC and cuKA histologies.
• S5 Data: Numerical data for graphs pertaining to Figure Panels Fig1A; Fig5A–E; Fig6A–B,D; Fig7C–G; Fig8A–B,D–F; Fig9A–I in the paper on the publicly availble PLOS Genetics Web site.