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1 Promoterless Transposon Drives Solid via Tumor Suppressor Inactivation

2 Aziz Aiderus1, Ana M. Contreras-Sandoval1, Amanda L. Meshey1, Justin Y. Newberg1,2, Jerrold M. Ward3, 3 Deborah Swing4, Neal G. Copeland2,3,4, Nancy A. Jenkins2,3,4, Karen M. Mann1,2,3,4,5,6,7, and Michael B. 4 Mann1,2,3,4,6,7,8,9

5 1Department of Molecular Oncology, Moffitt Center & Research Institute, Tampa, FL, USA

6 2Cancer Research Program, Houston Methodist Research Institute, Houston, Texas, USA

7 3Institute of Molecular and Cell , Agency for Science, Technology and Research (A*STAR), 8 Singapore, Republic of Singapore

9 4Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, 10 Maryland, USA

11 5Departments of Gastrointestinal Oncology & Malignant Hematology, Moffitt Cancer Center & Research 12 Institute, Tampa, FL, USA

13 6Cancer Biology and Evolution Program, Moffitt Cancer Center & Research Institute, Tampa, FL, USA

14 7Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, 15 USA.

16 8Donald A. Adam Melanoma and Skin Cancer Research Center of Excellence, Moffitt Cancer Center, Tampa, 17 FL, USA

18 9Department of Cutaneous Oncology, Moffitt Cancer Center & Research Institute, Tampa, FL, USA

19 These authors contributed equally: Aziz Aiderus, Ana M. Contreras-Sandoval, Amanda L. Meshey

20 These authors jointly supervised this work: Neal G. Copeland, Nancy A. Jenkins, Karen M. Mann, and 21 Michael B. Mann.

22 Correspondence to K.M.M. ([email protected]) or M.B.M. ([email protected]).

23 Present addresses: Foundation Inc., Boston, MA (J.Y.N.); Global VetPathology, Montgomery Village, 24 Maryland, USA (J.M.W.); and Genetics Department, University of Texas MD Anderson Cancer Center, 25 Houston, Texas, USA (N.G.C. and N.A.J.)

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26 Abstract

27 A central challenge in cancer genomics is the systematic identification of single and cooperating tumor 28 suppressor driving cellular transformation and tumor progression in the absence of oncogenic 29 driver (s). Multiple in vitro and in vivo inactivation screens have enhanced our 30 understanding of the landscape in various cancers. However, these studies are 31 limited to single or combination gene effects, specific organs, or require sensitizing . In this 32 study, we developed and utilized a Sleeping Beauty transposon mutagenesis system that functions only as 33 a gene trap to exclusively inactivate tumor suppressor genes. Using whole body transposon mobilization 34 in wild type mice, we observed that cumulative gene inactivation can drive tumorigenesis of solid cancers. 35 We provide a quantitative landscape of the tumor suppressor genes inactivated in these cancers, and 36 show that despite the absence of oncogenic drivers, these genes converge on key biological pathways and 37 processes associated with cancer hallmarks.

38 Key words: Sleeping Beauty transposon mutagenesis, tumor suppressor driver genes, Cul3, Rasa1, Trip12, 39 Ras signaling, E3 , and cancer hallmarks.

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40 INTRODUCTION

41 Recent genomic analysis of physiologically and histologically normal tissues such as eyelid epidermis and 42 esophageal squamous epithelia show that these tissues tolerate relatively high levels of mutations, 43 typically within known tumor suppressor genes (Martincorena et al., 2018; Martincorena et al., 2015; 44 Yokoyama et al., 2019). Sleeping Beauty (SB) (Ivics et al., 1997) is a powerful 45 forward genetic tool used to perform -wide forward genetic screens in laboratory mice for cancer 46 gene discovery (Collier and Largaespada, 2007; Copeland and Jenkins, 2010; Dupuy et al., 2005; Dupuy et 47 al., 2009; Mann et al., 2014a; Mann et al., 2016b; Mann et al., 2012; Mann et al., 2015; Mann et al., 2014b; 48 Rangel et al., 2016; Takeda et al., 2015). We recently conducted and reported an SB screen to model the 49 development of cutaneous squamous cell carcinoma in vivo, and noted that approximately 30% of tumors 50 formed without any oncogenic transposon insertions, albeit with extended latency. This finding raises 51 two questions: (i) can exclusive loss of tumor suppressor genes per se drive tumorigenesis? and (ii) how 52 do the kinetics of tumorigenesis in this context compare to tumors that develop via alterations in both 53 tumor suppressor and ?

54 In this study, we generated a series of new SB transposon alleles to explore the hypothesis that 55 cumulative loss of tumor suppressor genes is sufficient to drive the initiation and progression of systemic 56 tumorigenesis. To this end, we modified key features of an existing high copy pT2/Onc2 transposon allele 57 (Dupuy et al., 2005) and engineered a new transposon construct that functions as a gene trap to inactivate 58 . Whole body transposition of this modified high-copy, gene-trap transposon (pT2/Onc2.3 59 or SB-Onc2.3) via inducibly expressed SB was sufficient to initiate and progress a variety of 60 tumor types in vivo. Here, we prioritized solid tumors of the skin, lung and liver and employed high- 61 throughput SBCapSeq approaches (Mann et al., 2016b; Mann et al., 2015) to identify genome-wide SB 62 mutations and define recurrently mutated, statistically significant candidate cancer drivers (CCDs) from 63 bulk tumors containing more SB mutations expected by chance using the SB Driver Analysis (Newberg et 64 al., 2018a) statistical framework. We provide a quantitative genetic landscape of the transposon 65 insertions in these tissues and demonstrate that Ras signaling and members of the ubiquitin ligase 66 complex are frequently inactivated, suggesting key roles of these biological process and pathways during 67 the initiation and progression of solid cancers in the absence of selected oncogenic events.

68 RESULTS

69 Harnessing an SB gene-trap allele for forward genetic screens

70 Whole-body mutagenesis using high-copy, gene-trap only SB transposons in wild type mice

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71 We derived a novel gene-trap-only SB transposon allele, pT2/Onc2.3 (a.k.a. pT2/SB-GT-MBM102, Figure 72 1a), with two alterations to the pT2/Onc2 (Dupuy et al., 2005) transposon vector. First, the MSCV 5’LTR 73 and splice donor sequences were removed to disable the ability of the transposon to activate 74 gene expression upon integration into the promoter or intron regions of a gene. Second, an additional bi- 75 directional SV40-polyA signal sequence was added to enhance the transcriptional termination ability of 76 the transposon upon integration into genes. These changes shortened the Onc2.3 SB transposon cargo to 77 ~1.6 kb (Figure 1a), which matches the natural size of the original fish SB(Izsvak and Ivics, 2004) and 78 optimum size to maximize transposition in mammalian cells(Izsvak et al., 2000). Collectively, these 79 modifications result in an SB transposon that can only disrupt gene expression via inactivation, and 80 facilitates the identification of inactivated tumor suppressor genes that drive tumor initiation and 81 progression in vivo.

82 After pT2/Onc2.3 linearization (Supplementary Figure 1a) and into pronuclei, 83 56 of the resulting 101 live-born and weaned progeny were screened by Southern blot and found to carry 84 at least one copy of the transposon (Supplementary Figure 1b). We reasoned that mice with 85 the highest transgene copy number possible would allow for a maximal number of independent 86 integration events per cell, a strategy that facilitates identification of cooperating TSGs in malignant 87 transformation. Initially, five transgenic lines were selected to test for germ-line transmission by 88 backcross breeding to C57BL/6J mice (Supplementary Figure 1b). All five lines transmitted to offspring, 89 but only three T2/Onc2.3 lines, TG.14913, TG.14922, and TG.14942, segregated a transposon concatemer 90 as a discreet , suggesting they arose from a single event leading to high-copy concatemer integration 91 into the respective donor .

92 The three SB-Onc2.3 transgenic lines contain approximately the same number of copies as other T2/Onc2 93 high-copy lines, with estimated copy number of ~400 per transgene array (Supplementary Figures 2a- 94 b, 3a-b), and each line could be maintained as transgenic homozygotes without loss of viability, fertility, 95 or other obvious phenotypes. However, similar to what was observed with high-copy pT2/Onc2 carrier 96 mice(Dupuy et al., 2005), when combined with a constitutively active SBase allele all three T2/Onc2.3 97 transgenic lines had loss of viability with statistically significant reduced numbers of live-born double 98 heterozygous carriers (Supplementary Figure 4). To circumvent lethality in TG.14922 and TG.14942 99 lines, we used a conditional LSL SBase and Actb-Cre allele strategy (Aiderus et al., 2019; Mann et al., 2016b) 100 that fully restored viability in the resulting triple heterozygous carrier mice (Supplementary Figure 4a- 101 b). When combined with conditional LSL SBase and Actb-Cre alleles, T2/Onc2.3 transgenic carrier mice 102 (SB-Onc2.3 hereafter), exhibited high rates of whole-body transposition that resulted in tumor formation 103 (Figure 1b and Supplementary Figure 5a-c).

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104 Systemic, whole body Onc2.3 transposition extends latency of tumor development

105 We generated 107 SB-Onc2.3 (n=58 Actb-Cre|Onc2.3-TG.14942; n=49 Actb-Cre|Onc2.3-TG.14922) and 23 106 control (Actb-Cre|Onc2.3-TG.14922) mice and aged them for a maximum of 550 days (1.5 years). At the 107 predetermined endpoint, while only two control mice developed masses, many of the Onc2.3 developed 108 tumors (Figure 1b). Tumor-free survival of both SB-Onc2.3 cohorts was significantly reduced compared 109 to control cohorts (Kaplan-Meier log-rank test, P<0.0001, Figure 1b). Tumor latency was significantly 110 reduced in the TG.14922 cohort compared with the TG.14942 cohort (Kaplan-Meier log-rank test, 111 P<0.0001, Figure 1b) despite having indistinguishable tumor spectrums. Some of the mice censored in 112 the survival analysis were observed to have various cancers when necropsied and/or histologically 113 evaluated, suggesting our data represent a lower limit to the full tumor spectrum in SB-Onc2.3 mice.

114 The combined SB-Onc2.3 cohort exhibited a significantly longer mean tumor latency (Log rank test, 115 P<0.0001; Figure 1c) compared to similarly bred wild type SB-Onc2 (Mann et al., 2016b) or SB-Onc3 116 (Aiderus et al., 2019) cohorts. The tumor latency and spectrum of SB-Onc2.3 mice were more similar to 117 SB-Onc3 (Aiderus et al., 2019) mice, with few hematopoietic tumors and a similar wide variety of solid 118 tumor types, compared with SB-Onc2, including skin squamous cell carcinomas 119 (cuSCC)/keratoacanthoma (cuKA) and hepatocellular adenomas (HCA)/carcinomas (HCC) (Table 1 and 120 Supplementary Table 1). Unexpectedly, SB-Onc2.3 mice exhibited a significantly larger proportion of 121 early-stage, low-grade solid tumor types, including spinal cord and cerebellar astrocytomas (ACT) and 122 lung alveolar adenoma (LUAA) and adenocarcinoma (LUAC) (Supplementary Figure 6 and 123 Supplementary Table 1). However, with respect to transposon copy number, the average number of SB 124 insertions observed per tumor genome in SB-Onc2.3 mice was more similar to SB-Onc2 compared with 125 low-copy SB-Onc3 (Supplementary Figure 3-4), suggesting that copy-number per se does not explain the 126 differences in latency and tumor spectrum.

127 To better understand the genetic events driving these SB-Onc2.3 solid tumors, we generated genomic 128 libraries from a wide variety of SB-Onc2.3-induced solid cancers and used high-throughput SBCapSeq 129 (Mann et al., 2016b; Mann et al., 2015) to identify genome-wide SB insertions. Similar to previous 130 reported results in SB-Onc2(Mann et al., 2016b) and SB-Onc3(Aiderus et al., 2019), the SB-Onc2.3 131 libraries were highly reproducible (Supplementary Figure 7 and Supplementary Table 2).

132 Solid tumors driven by TSG inactivation in SB-Onc2.3 mice

133 Landscape of cuSCC driven by transposon-mediated tumor suppressor inactivation

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134 Skin tumors comprised 4% of the total number of tumors collected and histologically verified in SB- 135 Onc2.3 mice, suggesting that inactivation of tumor suppressor genes is sufficient to drive keratinocyte 136 initiation and progression to frank cuSCC in vivo. We recently reported in an SB-driven cuSCC model that 137 activating SB insertions into Zmiz1, Zmiz2, or Mamld1 oncoproteins are collectively observed in over two- 138 thirds of cuSCC tumors sequenced using SBCapSeq (Aiderus et al., 2019). This suggests that the initiation 139 and progression of approximately one-third of skin tumors in vivo do not require positive selection for 140 proto-oncogenes. We hypothesized that tumors without activating oncogenic insertions in the Zmiz1 or 141 Zmiz2 genes would have higher frequencies of inactivation of the tumor suppressor genes found in the 142 Onc2.3 system. We used SBCapSeq to quantitatively define the gene insertions in 6 SB-Onc2.3 skin tumors 143 with confirmed cuSCC diagnosis (Supplementary Tables 3-4) (Mann et al., 2016b). As expected, no 144 activating SB insertions greater than background rates (≥1 SBCapSeq read) were observed in the proto- 145 oncogenes Zmiz1, Zmiz2, or Mamld1 previously reported in our SB-Onc3-driven cuSCC or cuKA 146 cohorts(Aiderus et al., 2019). In contrast, the SB-Onc2.3 cuSCC tumors had recurrent, high read-depth 147 inactivating insertions in the Rasa1, Trip12, Cul3, Cux1, Tcf12, Nf1, Kmt2c, Ncoa2, and Crebbp genes 148 (Figure 2). Pathway analysis using Enrichr software (Chen et al., 2013; Kuleshov et al., 2016) and KEGG 149 database revealed enrichment of selected SB insertions in genes associated with MAPK signaling pathway 150 (Abl2, Nf1, Rasa1, Stk4; P=0.003) and Ras signaling pathways (Nf1, Rasa1, Stk4, Tgfb2; P=0.008). Based on 151 these data, we revisited our previously reported sequencing data from the SB|Onc3 cuSCC tissues 152 (Aiderus et al., 2019). Indeed, we observed that Zmiz1/2-negative cuSCC tumors had dramatically higher 153 inactivating SB insertions in Trip12, Kmt2c, Rasa1, Cul3 and Arid1b in ZMIZ1/2-negative cuSCC tumors 154 relative to ZMIZ1/2-positive cuSCC genomes (Figure 2). Notably, almost all (95%, 22/23) of the Zmiz1/2- 155 negative cuSCC contained single or cooperating mutations in those five genes (Figure 2), compared to 156 63% (27/43) of the ZMIZ1/2-positive cuSCC genomes. While the frequencies of individual gene hits 157 within the Zmiz1/2-negative cuSCC genomes derived from either Onc3 or Onc2.3 SB transposon lines 158 varied, similar cooperating relationships among the putative TSGs were conserved (Figure 2). We 159 conclude that the Onc2.3 transposon-derived skin tumors develop via cooperating inactivation of tumor 160 suppressor genes. This supports our prior observation that approximately one-third of SB-driven skin 161 masses are not driven by activating SB insertions in proto-oncogenes (Aiderus et al., 2019).

162 Landscape of lung cancer driven by transposon-mediated tumor suppressor inactivation

163 Approximately one-third of lung adenocarcinomas contain oncogenic mutation in KRAS (Suh et al., 2016), 164 and lung tumorigenesis is usually modeled in mice using oncogenic mutant Kras alleles as initiating 165 events (Haigis, 2017). Using SB mutagenesis, we successfully modeled lung alveolar adenoma (LUAA) and 166 adenocarcinoma (LUAC), demonstrating that oncogenic mutant Kras, or other strong oncogenic drivers, is 167 not required for lung tumor initiation in the mouse. To dissect the selected SB events driving early lung

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168 LUAA/LUAC tumorigenesis, we applied the SBCapSeq methodology to analyze the profiles of 169 tumors driven by the transposons Onc2.3 (Supplementary Table 5) or Onc3 (Supplementary Table 6; 170 previously reported (Aiderus et al., 2019)), which can either inactivate alone or activate and/or inactivate 171 gene expression, respectively, upon transposon insertion. In the Onc3 lung LUAA/LUAC tumors, 70% had 172 directional, activating insertions in Rasgrf1, encoding the guanine nucleotide exchange factor RASGRF1 173 which functions to activate Ras signaling by exchanging GDP for GTP (Figure 3, Supplementary Figure 174 8a-b, and Supplementary Table 6). Results from 454 sequencing confirmed activating Rasgrf1 175 insertions among the 29 Onc3 LUAA/LUAC tumors, including 10 large tumors from flash frozen genomic 176 DNA which were also sequenced by SBCapSeq, and 19 additional smaller tumors isolated from FFPE 177 tumor tissues (Supplementary Figure 9 and Supplementary Tables 7-9). In contrast, no insertions in 178 Rasgrf1 were observed in SB-Onc2.3 LUAA/LUAC tumors. Several genes including Rbms3, Sik3, Cul3, 179 Trip12, Rock1, Zfp292 and Rasa1 were more commonly inactivated in Onc2.3 compared to Onc3-driven 180 lung tumors. Pathway analysis using the Enrichr KEGG pathway analysis and biological 181 processes enrichment analysis revealed statistically significant enrichment of genes with SB insertions 182 associated with focal adhesion pathway (Rock1, Rasgrf1, Pten, and Pik3r1; P<0.0001), Ras signaling 183 pathway (Rock1, Rasgrf1, and Pik3r1; P<0.0001) and regulation of protein ubiquitination (Cul3 and 184 Trip12; P=0.001). Notably, Cul3 and Trip12 — members of the E3 ubiquitin ligase complex — were 185 exclusively inactivated in the Onc2.3 but not Onc3–driven lung tumors. Among the targets of TRIP12 is 186 ASXL1, a tumor suppressor with roles in Polycomb-induced gene silencing. Two SNVs in Asxl1 were 187 identified in mouse lung adenomas induced by MNU in the background of a KrasG12D mutation (Westcott 188 et al., 2015). Izumchenko et al. described mutations in ASXL1 and other genes involved in DNA damage 189 and chromatin remodeling identified in the lungs of patients with atyptical adenomatous 190 hyperplasia, an initiating event in adenocarcinoma development(Izumchenko et al., 2015). RBMS3, RNA 191 Binding Motif Single Stranded Interacting 3, is a validated TSG in human lung SCC where it acts 192 primarily via regulation of c-Myc (Liang et al., 2015). CUL3 is a promiscuous E3 ubiquitin ligase that 193 partners with multiple to regulate protein turnover of many targets in a context specific manner. 194 CUL3 plays an important role in ubiquitination of KEAP1, a negative regulator of the factor 195 NRF2 which enacts a transcriptional program important in protecting lung cancer and other tumor types 196 from oxidative stress (Zhang et al., 2005). These data suggest that in the Onc3–driven lesions, activation 197 of Rasgrf1 contributes to rapid lung tumorigenesis, while in Onc2.3–driven lung tumorigenesis, the 198 inactivation of cooperative tumor suppressor genes drives disease after long latency, potentially through 199 modulating protein turnover and transcriptional reprogramming. Further studies are needed to show 200 whether these mechanisms may represent functional redundancy with key pathways initiated by 201 oncogenic Kras to promote lung cancer in mice. 202

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203 Landscape of liver cancer driven by transposon-mediated tumor suppressor inactivation

204 Previously we generated hepatocellular adenomas (HCAs) and adenocarcinomas (HCC) driven by the SB- 205 Onc3 transposon in the presences of mutant or wild type Trp53 alleles (Newberg et al., 2018a; Newberg et 206 al., 2018b). From 95 histologically confirmed HCAs (HCA; Supplementary Table 2), we identified 43 207 trunk drivers, including proto-oncogenes Hras, Kras, Rlt1/Rian and tumor suppressor genes Pten, Adk, 208 and Zbtb20 (Supplementary Tables 10–12). Most of these genes were identified in Trp53 mutant and 209 wild type cohorts, suggesting that their role in driving HCA is Trp53-independent. Further, the majority of 210 the putative driver genes identified in our HCA tissues were also reported in SB-driven hepatocellular 211 carcinoma (HCC)(Bard-Chapeau et al., 2014; Dupuy et al., 2009; Keng et al., 2013; O'Donnell et al., 2012; 212 Rogers et al., 2013), suggesting that many of the initiating genes enriched during earlier stages of 213 hepatocyte transformation in vivo are maintained in HCC (Supplementary Fig. 10). SBCapSeq analysis of 214 the 4 HCA and 2 HCC tumors from SB-Onc2.3 mice revealed no activating insertion patterns in the 215 genomes from these tumors and the absence of hits in Hras, Kras, and Rlt1/Rian (Supplementary Table 216 13). However, we corroborated the tumor-suppressive roles of insertions in Adk and Zbtb20, and in 217 Nipbl, Pdlim5, Ppp1r12a, Tnrc6b, Brd4, Cul3, Ctnna3, Elavl1, Gphn, Nfia, Ptpn12, Taok3, and Rasa1 (Figure 218 4). Using Enrichr KEGG pathway analysis and gene ontology biological processes enrichment analysis 219 revealed statistically significant enrichment of genes with SB insertions associated with ubiquitin 220 mediated proteolysis (Cul3, Cul5, and Trip12; P<0.0001), growth factor signaling (Ep300, Itgb1, and Rasa1; 221 P<0.001), scaffolding proteins involved in cell adhesion (Dlg1, Itgb1, and Pdlim5; P<0.001), and 222 transcriptional regulators (Brd4, Med13l, Nfia, and Nipbl; P<0.0001). Notably, the inactivation of RASA1 223 suggests that the Onc2.3 transposon may activate Ras signaling via inactivation of the negative regulator 224 of this pathway, in the absence of oncogenic Ras activation. Taken together, by using different transposon 225 systems, we show that HCA in mice can be initiated by activation of oncogenes in combination with tumor 226 suppressor inactivation, or exclusively by inactivation of cooperating tumor suppressors that converge on 227 similar mechanisms co-opted to promote tumorigenesis.

228 Landscape of other solid tumors driven by transposon-mediated tumor suppressor inactivation

229 Finally, we conducted SBCapSeq analysis on nine other SB-Onc2.3 mouse tumors from diverse tissues and 230 histological classifications, including three ovarian tumors (with adenoma, papillary, and granulosa cell 231 carcinoma subtypes), a uterine adenocarcinoma, a cerebellar astrocytoma, a colon polypoid adenoma, a 232 preputial gland carcinoma, a renal tubular cell adenoma, and a Schwannoma of the cerebellum. 233 Individually, all but one specimen demonstrated reproducible (Supplementary Table 3) and clonal SB 234 insertions sites, as evidenced by a range of low to very high read-depth-enriched TA-dinucleotide sites 235 within the coding region of many known tumor suppressor genes such as Apc, Brd4, Cul3, Cux1, Gnaq, Nf1,

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236 Pten, Rasa1, Rnf43, and Wac (Supplementary Table 14-15). Notably, the astrocytoma sample presented 237 no evidence of clonal selection, despite exhibiting the highest total number of SBCapSeq reads. This 238 suggests that this mass may have other non-SB driven mechanisms contributing to tumor initiation (see 239 Supplementary Note 1). Collectively, these results strongly suggest an SB-driven etiology, consistent 240 with the studies in skin, lung, and liver described above, and in multiple previously reported studies 241 (Aiderus et al., 2019; Mann et al., 2016b; Mann et al., 2012; Mann et al., 2015; Newberg et al., 2018a; 242 Newberg et al., 2018b; Rangel et al., 2016; Takeda et al., 2015).

243 Common pathways selected in response to whole genome tumor suppressor gene inactivation

244 We observed Brd4, Cul3, and Trip12 to be commonly mutated genes across different tumor types, 245 suggesting that there may be common mechanisms perturbed by the Onc2.3 transposon to drive 246 tumorigenesis in the absence of oncogenic events. Therefore, we extended our analysis to statistically 247 define recurrent tumor suppressor genes across 27 SB-Onc2.3 tumors using SB capture sequencing 248 (Mann et al., 2016b) and SB Driver analysis (Newberg et al., 2018a) (Supplementary Table 16-18). We 249 reasoned that regardless of the tumor origin, a meta-analysis of selected SB insertion events enabled by 250 the SB Driver Analysis (Newberg et al., 2018a) workflow may provide a quantitative means to explore the 251 detection of potentially novel, cooperative TSGs. We identified 1,499 discovery-significant progression 252 drivers, 476 genome-significant progression drivers (Supplementary Table 17), and 53 genome- 253 significant trunk drivers (Supplementary Table 18) using the SB Driver Analysis statistical categorical 254 framework (Newberg et al., 2018a) (see Methods). As expected, none of the sense-strand-oriented, 255 recurrent SB insertions present in defined proto-oncogenes from tumors driven by SB transposons 256 containing an internal promoter (see the SBCDDB (Newberg et al., 2018a; Newberg et al., 2018b)) were 257 identified in any of the SB-Onc2.3 tumors. Further, meta-analysis using SB Driver Analysis, including all 258 SB-Onc2.3 (n=27) and SB-Onc3 (n=10) lung tumors, showed that Rasgrf1 was the only gene identified 259 with an activating SB insertion pattern (Supplementary Table 19).

260 The Cancer Gene Census (COSMIC v91 (Bamford et al., 2004; Forbes et al., 2010; Sondka et al., 2018)) 261 contains 313 genes with a designation of TSG and a unique mouse ortholog (Supplementary Table 20). 262 The Onc2.3-Pan-TSG dataset contains 1,499 driver genes. We observed 78 genes in common between the 263 CGC and the Onc2.3-Pan driver genes, which represent a statistically significant enrichment of shared 264 genes than expected (Supplementary Table 20; Chi-square with Yates' correction, χ2=104.742, two- 265 tailed P<0.0001). This suggests that the genes identified in our screen are enriched for known TSGs that 266 driver tumorigenesis. Selective and statistically significant enrichment of the Onc2.3-Pan-TSG dataset was 267 also observed with the 1,004 TSGs listed in the Tumor Suppressor Gene Database (Zhao et al., 2016; Zhao 268 et al., 2013) with a unique mouse orthologs. We observed 127 genes in common between the TSGdb-

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269 orthologs and the Onc2.3-Pan driver genes, which represent a statistically significant enrichment of 270 shared genes than expected (Supplementary Table 21; Chi-square with Yates' correction, χ2=32.662, 271 two-tailed P<0.0001). Overall, 167 known TSGs were identified in the Onc2.3-Pan-TSG dataset, suggesting 272 that the additional 1,333 remaining genes may represent potential novel TSG drivers (Figure 7), 273 including Trip12, Rbm33, and Zfp292, with recurrent SB insertion sites in Onc2.3 tumors demonstrated 274 insertion patterns predicted to inactivate target gene expression. Indeed, although not represented on 275 either of the curated CGC or TSGdb lists, several genes (e.g., Cep350 (Mann et al., 2015), Ncoa2 (Aiderus et 276 al., 2019; O'Donnell et al., 2012), and Usp9x (Perez-Mancera et al., 2012)) have all been observed in other 277 SB tumor screens and experimentally validated to be TSGs within mouse models and/or human cancer 278 cells.

279 To gain further insights into novel pathways that lead to tumor initiation and/or progression via 280 cooperating TSG only routes, we performed Enrichr biological pathway enrichment analysis (Chen et al., 281 2013; Kuleshov et al., 2016) using the 1,499 Onc2.3-Pan-TSG-Drivers. We observed overrepresentation of 282 the Onc2.3-Pan-TSG-Drivers among the top 1% of all known biological processes with statistically 283 significant enrichment in known pathways involved in cancer initiation and progression, including AR, 284 EGF/ERGR, TGF-beta, PDGFB, mTOR, and VEGF signaling pathways, ubiquitin mediated proteolysis, 285 chromatin modifying and organization, and RHO GTPase effectors (Supplementary Table 22). 286 Similarly, Enrichr gene ontology enrichment analysis reaffirmed our manual curation, namely that genes 287 with roles in diverse processes, including protein ubiquitination, cadherin binding, focal adhesion, and 288 chromatin, are over-represented among the top 1% of all known biological processes (Supplementary 289 Table 22). We conclude that this set of known and suspected TSGs represents a rich resource for 290 prioritizing future efforts to catalogue the genes in the cancer genome that can drive tumor initiation 291 and/or progression without oncogenic mutations.

292 DISCUSSION

293 In this study, we investigated whether in vivo tumor initiation and progression was possible solely by 294 inactivation of tumor suppressor genes. We generated a new SB transposon allele that lacks the internal 295 promoter present in all SB transposons used to-date in mouse models of cancer(Collier et al., 2005; 296 Copeland and Jenkins, 2010; Dupuy et al., 2005; Dupuy et al., 2009; Newberg et al., 2018a; Newberg et al., 297 2018b). Here, we demonstrate that the Onc2.3 transposon restricts SB mutagenesis to act as a gene trap, 298 selectively inactivating genes. While SB genetic screening studies have reported tumor suppressor genes 299 in mouse models of cancer, these screens have often been conducted using strong oncogenic initiating 300 mutations, including KrasG12D (Mann et al., 2012; Perez-Mancera et al., 2012), BrafV600E (Mann et al., 2015; 301 Perna et al., 2015) and Apc loss (Starr et al., 2009; Takeda et al., 2015) or HBV expression (Bard-Chapeau

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302 et al., 2014). Importantly, we demonstrate that our Onc2.3 transposon system enables the evaluation of 303 tumorigenesis in vivo by exclusive loss of tumor suppressor genes without introduction of an initiating 304 (Katigbak et al., 2016; Zender et al., 2008). Notably, whole-body mutagenesis using the Onc2.3 305 transposon resulted in distinct cell types that were more susceptible to tumorigenesis than others. This 306 may be due to the fact that exclusive tumor suppressor gene inactivation leads to a longer tumor latency 307 in some tissues, or that some cell types in the mouse have robust mechanisms to withstand tumorigenesis 308 without an exogenous or induced oncogenic hit. This latter phenomenon has been well-documented in 309 the literature, particularly for mouse models of human cancers driven by oncogenic sensitizing events, 310 including melanoma, pancreatic and colon cancers (Mann et al., 2012; Mann et al., 2015; Newberg et al., 311 2018a; Newberg et al., 2018b; Takeda et al., 2015), notably absent from the observed tumor types with 312 the Onc2.3 promoterless transposon.

313 Mutagenesis methods to study skin tumorigenesis typically rely on inducing point mutations that target 314 both tumor suppressors and oncogenes (Abel et al., 2009; Chitsazzadeh et al., 2016; Molina-Sanchez and 315 Lujambio, 2019) or insertional mutations without point mutations (Mann et al., 2016b; Mann et al., 2015). 316 In cuSCC tumors driven by the SB-Onc2.3 transposon, we noted a high frequency of gene inactivation in 317 chromatin remodelers. This suggests that in the absence of an oncogenic hit, inactivation of chromatin 318 remodeler genes can drive cuSCCs, presumably due to their dynamic ability to regulate expression of 319 genes, miRNAs and lncRNAs involved in different biological processes and pathways intimately involved 320 in tumorigenesis. Indeed, inactivation of chromatin remodeler genes has been shown to drive the 321 initiation and progression of many different cancers (Andricovich et al., 2018; Cho et al., 2018; Dhar et al., 322 2018; Jia et al., 2018; Mathur et al., 2017; Wu et al., 2018). We recently reported functional evidence that 323 shRNA-mediated knockdown of KMT2C or CREBBP in immortalized primary human keratinocytes was 324 sufficient for cell transformation in vitro but was insufficient to promote tumor growth in vivo, suggesting 325 that cuSCC development requires additional cooperating oncogenic events(Aiderus et al.). This is 326 supported by the recent findings of Ichesi et al. who reported that heterozygous loss of Crebbp alone, or 327 together with heterozygous loss of its paralog Ep300, cooperates with mutant Ras to drive keratinocyte 328 hyper-proliferation in vivo (Ichise et al.). Furthermore, a recent genetic screen demonstrated that 329 inactivation of Fbxw7 or Slc9a3 could transform mouse embryonic fibroblasts cells in vitro within the 330 context of oncogenic KrasG12D, but was not sufficient to form tumors in vivo (Huang et al.). Our SB-Onc2.3 331 is also of relevance to human cuSCC, as the majority of patients are older individuals, and recent studies 332 indicate that cancer driver mutations are tolerated in physiologically normal squamous tissues, even in 333 relatively younger individuals (Martincorena et al., 2018; Martincorena et al., 2015). This is consistent 334 with the observation in both this study (using SB-Onc2.3) and our previous study (using SB-Onc3)

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335 (Aiderus et al., 2019) that cumulative tumor suppressor inactivation over time may be an important and 336 under recognized route to keratinocyte transformation initiation and cuSCC progression.

337 In both cuSCC and liver tumors, inactivation of the Rasa1 gene, encoding a RAS-inhibiting GTPase, was a 338 frequent, recurrent event. Rasa1 inactivation was observed in a previous SB study investigating resistance 339 mechanisms to FGFR inhibition in invasive lobular (Kas et al.). Our data suggests that Ras- 340 mediated MAPK-ERK signaling may play a role in driving both cuSCC and hepatocellular adenocarcinoma. 341 In support of this, the Onc2.3-driven cuSCCs also exhibited inactivation of Nf1, encoding a negative 342 regulator of Ras signaling important in many cancer types. Mutations in RASA1 and NF1 co-occur in 343 human non-small cell lung cancer (Hayashi et al.), which may reflect independent mechanisms by which 344 RASA1 and NF1 inhibit RAS or the clonal diversity within these tumors that preferentially selects one of 345 these mechanisms.

346 The majority of the putative driver genes identified in HCA driven by Onc2.3 were also reported in SB- 347 driven hepatocellular carcinoma (HCC)(Bard-Chapeau et al., 2014; Dupuy et al., 2009; Keng et al., 2013; 348 O'Donnell et al., 2012; Rogers et al., 2013), supporting the role for these events in HCC initiation. While we 349 did not identify SB inaction of Ncoa2 and Sav1 in our tumors, these genes were previously identified in 350 liver cancer mouse models driven by SB mutagenesis in the presence of Myc activation or Pten loss 351 (Kodama et al., 2018; O'Donnell et al., 2012). It is likely that initiating oncogenic events influence the 352 evolutionary routes of tumor development, dictating the selection and maintenance of cooperating 353 drivers. The extent to which context-dependent SB insertion events impact tumor development remains 354 to be determined. Our HCA/HCC data suggests that while tumors initiated by an oncogenic mutation may 355 exhibit shorter tumor latencies than tumors lacking exogenous initiating oncogenic events and may have 356 distinct subsets of inactivated genes, both populations converge on similar signaling pathways. 357 Importantly, the frequent development of cuSCC and HCA using the Onc2.3 SB transposon demonstrates 358 that tumor suppressor gene inactivation is sufficient for de novo transformation of both keratinocytes or 359 hepatocytes in vivo.

360 When all the Onc2.3 tumors were analyzed together, we noted that the negative regulators of the Ras 361 signaling pathway such as Rasa1 and Nf1 were commonly inactivated in liver and cuSCC, while genes 362 encoding members of the E3 ubiquitin ligase such as Trip12 and Cul3 were frequently inactivated in all 363 tumor types analyzed. Additionally, in cuSCC tumors without activation of the Zmiz proto-oncogenes, the 364 frequency of Trip12 and Cul3 inactivation were markedly increased, relative to tumors with Zmiz 365 oncogene activation. The E3 ubiquitin ligase-proteasome have diverse roles, including regulating the Ras, 366 MAPK, and PI3K/Akt signaling pathways, gene expression and cell death (Senft et al., 2018). This range of 367 biological processes may explain why Trip12 and Cul3 inactivation is frequently observed in the Onc2.3

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368 tumors. Indeed, a previous Sleeping Beauty screen by Dorr et al. using the Onc2 transposon system also 369 found inactivation in Cul3 (Dorr et al., 2015). The authors functionally validated the tumor suppressive 370 role of CUL3 in A549 and H522 human lung cancer cell lines, and showed that shRNA knockdown of this 371 gene increased proliferation rates, relative to control. The second E3 ligase associated gene Trip12 372 observed in our screen has been shown to be essential in the regulation of the cell cycle (Larrieu et al.).

373 Our Onc2.3 model is not without limitations. First, in cuSCC tumors, it is not clear why we did not observe 374 inactivation of tumor suppressors frequently described in human squamous epithelium such as TP53 and 375 NOTCH1. Inactivation of NOTCH1 has been postulated to drive the evolutionary dead-end of nascent pre- 376 cancerous population of cells (Higa and DeGregori). This is based on the observation that the frequency of 377 NOTCH1 mutations decreases in esophageal and skin cancers, relative to physiologically normal epithelial 378 tissues (Higa and DeGregori, 2019; Martincorena et al., 2018; Yokoyama et al., 2019). Consistent with this, 379 in our previously reported Onc3 screen, we noted that the frequency of Notch1 inactivation was 380 decreased in cuSCC versus keratoacanthoma tissues, suggesting that Notch1 loss is not essential for cuSCC 381 development (Aiderus et al.). While we did not observe inactivation of Trp53, our previous Onc3 screen 382 suggests that there were no obvious differences in the insertion profiles of tumors with either mutant or 383 wild type Trp53 background, albeit the rate of tumorigenesis was significantly reduced in Trp53 mutant 384 mice. Additionally, as noted in the SB Cancer Driver Database, the low frequency of transposon-driven 385 Trp53 inactivation is not unique to our study, and has been observed in other SB screens reported to date 386 (Newberg et al.). Second, we noted that genes involved in chromatin remodeling were inactivated in all of 387 the tumor types sequenced, albeit at different frequencies. It is possible that loss of these tumor 388 suppressors may activate oncogene expression, thereby promoting tumorigenesis. However, given the 389 significantly extended latency of tumor development in the Onc2.3 mice, it is unlikely that such genes 390 confer strong advantage in clonal expansion, and the chromatin remodeler loss likely affects tumor 391 suppressive processes. Similarly, without genomic sequencing analysis, we cannot exclude the possibility 392 that spontaneous driver mutations that confer cooperating oncogenic and/or tumor suppressive 393 alterations, are also contributing to the Onc2.3-driven tumors analyzed in this study. However, extensive 394 genomic analyses of whole genome, exome or transcriptome from SB-driven melanoma(Mann et al., 2015; 395 Perna et al., 2015), myeloid leukemia (Mann et al., 2016b) and cuSCC (Aiderus et al., 2019) have revealed 396 very few non-transposon derived alterations, including any known or suspected oncogenic events. Last, in 397 this study, we focused only on determining the transposon insertion profiles across various tumor types. 398 The inactivation of genes involved in chromatin remodeling and protein ubiquitination suggests the 399 necessity to profile the transposon mutagenesis-driven tumors on other platforms (e.g., transcriptome, 400 proteome) to gain a more comprehensive understanding of the molecular events driving tumorigenesis.

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401 Collectively, our data strongly implicate routes to tumorigenesis via cooperative inactivation of tumor 402 suppressor driver genes alone, and precludes the necessity of oncogenic events. The dramatic reduced 403 penetrance and increased latency of skin, lung, and liver tumors when subjected to systemic gene-trap 404 only transposon mutagenesis, highlights three important points: i) gene inactivation per se is sufficient to 405 drive de novo transformation in vivo of keratinocytes, lung alveolar epithelium, and hepatocytes and 406 tumor initiation in vivo; ii) transformation by gene inactivation alone is likely to be the exception rather 407 than rule as penetrance of proto-oncogenic driven cuSCC, LUAC, and HCA is substantially higher, and iii) 408 cuSCC development has no absolute requirement for oncogenic drivers (e.g., activating ZMIZ or RAS 409 oncoproteins), and can occur via cumulative inactivation of tumor suppressors, which in either instance, 410 converge on similar altered cancer hallmark signaling pathways. Thus, we conclude that the SB-Onc2.3 411 model delivers a novel in vivo platform that allows systemic gene inactivation in a non-sensitized 412 background, provides a heterogeneous background that promotes evolutionary routes to tumorigenesis.

413 Author Contributions

414 M.B.M., K.M.M. N.G.C., and N.A.J. conceived the project and provided laboratory resources and personnel 415 for animal husbandry, specimen archiving, sequencing and compute management. M.B.M. and K.M.M. 416 designed the studies, directed the research, interpreted the data, performed experimental work, 417 coordinated sequencing, and analyzed the data. A.A., A.M.C.-S., and A.L.M. performed and/or analyzed 418 experimental datasets, including optimizing capture hybridizations for the SBCapSeq experiments. J.Y.N. 419 and M.B.M. performed statistical and bioinformatics analyses. J.M.W. performed and directed veterinary 420 pathology analysis, including tumor grading and diagnosis. D.S. generated the high-copy T2/Onc2.3 421 transgenic founder mouse lines. A.A., K.M.M. and M.B.M. wrote the manuscript. All co-authors approved 422 manuscript before submission.

423 Competing financial interests. The authors have no competing financial interests to declare.

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SB Cohort SB-Onc2.3 SB-Onc3 SB-Onc2 Promoter no promoter CAG promoter MSCV promoter Reference This study Aiderus et al. , 2019 Mann et al. , 2016 Tumor classification tumors mice tumors mice tumors mice Skin Squamous Cell Carcinoma 5 4 (3%) 52 20 (24%) 0 0 (0%) Skin Keratoacanthoma 1 1 (1%) 9 8 (10%) 0 0 (0%) Hepatocellular Carcinoma 2 2 (2%) 9 9 (11%) 0 0 (0%) Hepatocellular Adenoma 4 3 (2%) 79 42 (50%) 0 0 (0%) Adenoma, Multiple 25 16 (12%) 39 31 (37%) 0 0 (0%) Adenocarcinoma, Multiple 3 3 (2%) 9 8 (10%) 0 0 (0%) Carcinoma, Multiple 0 0 (0%) 6 6 (7%) 0 0 (0%) Sarcoma 0 0 (0%) 6 6 (7%) 0 0 (0%) Papilloma 1 1 (1%) 4 3 (4%) 0 0 (0%) Astrocytoma 34 34 (26%) 3 3 (4%) 0 0 (0%) Hemangiosarcoma 0 0 (0%) 3 3 (4%) 0 0 (0%) Hemangioma 1 1 (1%) 2 2 (2%) 0 0 (0%) Fibrosarcoma 0 0 (0%) 2 2 (2%) 0 0 (0%) Metastasis 0 0 (0%) 2 2 (2%) 0 0 (0%) Mast Cell Tumor 0 0 (0%) 1 1 (1%) 0 0 (0%) Trichoepithelioma 0 0 (0%) 1 1 (1%) 0 0 (0%) Schwannoma 1 1 (2%) 0 0 (0%) 0 0 (0%) Hepatoblastoma 1 1 (1%) 0 0 (0%) 0 0 (0%) Medulloblastoma 0 0 (0%) 0 0 (0%) 6 6 (8%) Lymphoma 1 1 (2%) 2 2 (2%) 28 28 (36%) Leukemia 0 0 (0%) 0 0 (0%) 78 78 (100%) Histocytic Sarcoma 0 0 (0%) 8 8 (10%) 0 0 (0%) Totals 79 107 237 87 112 78 Average tumors per mouse 0.74 2.72 1.44 Average tumor latency (days) 450 330 70 424

425 Table 1: SB allele-specific tumor spectrum by whole-body, transposon-mediated mutagenesis 426 in wild type mice. Distribution of cancer types between promoter-driven (SB-Onc3, SB-Onc2) and 427 promoter-less (SB-Onc2.3) transposons. Complete Table 1 source data may be downloaded from Figshare 428 http://dx.doi.org/10.6084/m9.figshare.12811685.

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a

SA En2-SA 2×SV40- SB:T2/Onc2.3 polyA (TG.14922 or TG.14942)

~1.6 kb

SA MSCV SD En2-SA SB:T2/Onc2 SV40- polyA (TG.6070 or TG.6113)

~2.1 kb

SA CAG SD En2-SA SB:T2/Onc3 SV40- polyA (TG.12740)

~2.2 kb

b 100

P<0.0001 75 Log-rank test (Mantel-Cox)

50 Tumor-free survival (%) 25 Actb-cre | Onc2.3–TG.14922 (n=23) Actb-cre | Onc2.3–TG.14942 | LSLSBase (n=58) Actb-cre | Onc2.3–TG.14922 | LSLSBase (n=49) 0 0 50 100 150 200 250 300 350 400 450 500 550 600 Age (d) c

100

P<0.0001 75 Log-rank test (Mantel-Cox)

50

Tumor-free survival (%) LSL 25 Actb-cre | Onc2 | SBase (n=78) Actb-cre | Onc3 | LSLSBase (n=87) Actb-cre | Onc2.3 | LSLSBase (n=107)

0 0 50 100 150 200 250 300 350 400 450 500 550 600 Age (d) 429

430 Figure 1: Whole-body, gene-trap exclusive SB transposon mutagenesis results in tumor formation 431 in SB-Onc2.3 mice. (a) Comparing Sleeping Beauty transposons used in this study (T2/SB-GT, T2/Onc3) 432 or in a similar companion study (T2/Onc2). Abbreviated allele designations for founder lines used in this 433 work are shown to the right of each vector. (b) Kaplan-Meier survival plots comparing experimental and 434 control SB-Onc2.3 cohorts (Mantel-Cox log-rank test, P < 0.0001, Supplementary Figure 1). Mice in all 435 SB-Onc2.3 cohorts with active SB mobilization developed solid tumors at multiple organ sites, however 436 SB-Onc2.3-TG.14922 mice (orange line) had significantly decreased survival compared to the SB-Onc2.3- 437 TG.14942 mice (purple line; Mantel-Cox log-rank test, P = 0.0015). (c) Kaplan-Meier survival plots 438 comparing the relative tumor latency between various SB cohorts with whole-body mobilization by a 439 conditionally activated from the Rosa26-LSLSBase allele to the Rosa26-1lox-SBase allele by whole body 440 Beta-actin-driven Cre expression, including SB-Onc2 mice (combined data from TG.6070 and TG.6113 441 alleles containing an MSCV-promoter (Mann et al., 2016b)), SB-Onc3 (data from TG.12740 allele 442 containing a CAG-promoter (Aiderus et al., 2019)), and SB-Onc2.3 (combined data from TG.14922 and 443 TG.14922 alleles containing no promoter) (Mantel-Cox log-rank test, P < 0.0001, Table 1).

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Zmiz1/Zmiz2 negative cuSCC genomes Zmiz1/Zmiz2 positive genomes

Onc2.3 Onc3 Onc3

Trip12

Tcf12

Cul3

Rere

Vps13b

Rasa1

Zfp148

Hnrnpm

Ptprc

Adgrb3

Akap13

Cnot1

Cnot2

Cux1

Dennd1b

Dpp10

Utrn

Ythdc1

Cltc

Fam168b

Kansl1l

Bmpr2

Nf1

Kmt2c

Ncoa2

Crebbp

Notch1

PicalmTrip12 16%

Diap2Rasa1 23% Foxj3 Cul3 16% Fto Arid1b 28% Rc3h1 Crebbp 26% Aida Ncoa2 33% Arnt Kmt2e 21% Ebf1

Zfhx4Ncor2 9%

Kmt2c 23%

Genetic AlterationAlteration 444 No alterations AmplificationActivating DeepInactivating Deletion

445 Figure 2: SB-driven cuSCC by cumulative tumor suppression. (a) Recurrent inactivating SB insertions 446 in Onc2.3-induced cuSCC genomes (n=6). (b) Comparative waterfall plots of trunk driver genes from 447 Zmiz1/Zmzi2-independent SB-Onc2.3 and SB-Onc3 (n=23; left panel) and Zmiz1/Zmzi2-dependent SB- 448 Onc3 (n=43; right panel) cuSCC tumors. (c) Zmiz1/Zmiz2-independent tumor segregated by SB cohort, 449 SB-Onc3 (n=17; left panel) and SB-Onc2.3 (n=6; right panel).

Aiderus, Contreras, Meshey, et al., 2020 17 6/16/2020 SB%7CP53%7CLung-454-SB Drivers-oncoprint.svg

Trp53 mice 100%

Rasgrf1 28%

Ptprd 48%

Rbms3 34%

Dopey1 34%

Astn2 28%

bioRxiv preprint doi:Trip12 https://doi.org/10.1101/2020.08.17.25456524% ; this version posted August 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made Nfia 24% available under aCC-BY-NC-ND 4.0 International license.

Ube2cbp 24% Onc2.3 13%Onc2.3 Onc2.313% 13%

RngttOnc3 21%22%Onc3 Onc322%SBCapSeq22% 454T_seq

Stag1Onc3-454 21%64%Onc3-454Onc2.3Onc3-45464% 64% Onc3 Onc3 Rasgrf1Rasgrf1 33%Rasgrf10% Rasgrf133% 70% 33% 28% Setd2 21% Rbms3Rbms3 100%40%Rbms3 Rbms340% 20% 40% 34% Rdx 21% Sik3Sik3 67%24%Sik3 Sik324% 30% 24% 14% Tnr 21% Cul3Cul3 83%13%Cul3 Cul313% 0% 13% 3% Rabgap1lTrip12Trip12 21%83%24%Trip12 Trip1224% 0% 24% 21%

Kmt2e 11%Kmt2e Kmt2e11% 11% Nf1Kmt2e 17%67% 10% 0% Rock1Rock1 83%18%Rock1 Rock118% 0% 18% 10% Tcf12 17% Zfp292Zfp292 67%18%Zfp292 Zfp29218% 10% 18% 10% Arhgap42 17% Zfp618Zfp618 67%16%Zfp618 Zfp61816% 10% 16% 7% Fam214aAnkrd44Ankrd44 17%50%18%Ankrd44 Ankrd4418% 10% 18% 14%

Rfwd2Rasa1Rasa1 17%50%16%Rasa1 Rasa116% 10% 16% 10% Brd4 9%Brd4 Brd49% 9% 0% Pde4bBrd4 17%67% 0% PtenPten 67%18%Pten Pten18% 0% 18% 14% Mbnl1 17% Pik3r1Pik3r1 50%9%Pik3r1 Pik3r19% 10% 9% 0% Rfx7 17% NptnNptn 33%13%Nptn Nptn13% 20% 13% 7% Cdk5rap2Trp53Trp53 genotype17%100%Trp53 Trp53100% 100%

Genetic AlterationGenetic AlterationGenetic InframeAlteration Mutation (unknownInframe Mutation significance)Inframe (unknown Mutation significance)Missense (unknown Mutation significance)Missense (unknown Mutation significance)Missense (unknown Mutation significance)Truncating (unknown Mutation significance)Truncating (unknown Mutation significance)Truncating (unknown Mutation significance)Fusion (unknown significance)Fusion Fusion Genetic Alteration Trp53 WT Trp53 KO/+ Trp53 R172H/+ Activating Inactivating No alterations 450 Amplification AmplificationDeep Deletion AmplificationDeepNo DeletionalterationsDeepNo Deletion alterations No alterations

451 Figure 3: SB-driven lung cancer by cumulative tumor suppression. Recurrent inactivating SB 452 insertions in Onc2.3 (n=6 using SBCapSeq) and Onc3 (n=10 using SBCapSeq; n=29 using 454T 453 sequencing) induced LUAA genomes.

file:///Users/mannmb/Desktop/SB%7CP53%7CLung-454-SB Drivers/SB%7CP53%7CLung-454-SB Drivers-oncoprint.svg 1/1

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Kras/Hras/Rtl1 negative cuSCC genomes Kras/Hras/Rtl1 positive genomes

Onc2.3 Onc3 Onc3 Brd4 Zfand3 Elavl1 Slmap Mkl2 Cul3

Adk

Dlg1 Zbtb20

Gphn Taok3 Pum1

Ppp1r12a Nipbl

Cd2ap

Ankrd17 Nfia

Zfr Zfp148 Tmcc1

Ep300 Fto Rasa1 Tnrc6b

Tlk1 Whsc1l1 Rfwd2

Mllt10 Yme1l1

Ahcyl1 Med13l Acap2 Trip12 16% Ptpn12 Plcb1 Rasa1 23%

Pdlim5 Cul3 16% Zfhx3 Arid1b 28% Aftph Crebbp 26% Pid1 Prpf40a Ncoa2 33%

Tsc22d2 Kmt2e 21% Atad2b Ncor2 9% Caprin1 23% Itgb1 Kmt2c

Genetic AlterationAlteration 454 No alterations AmplificationActivating DeepInactivating Deletion

455 Figure 4: SB-driven liver cancer by cumulative tumor suppression. Recurrent inactivating SB 456 insertions in Onc2.3 (n=6 using SBCapSeq) and Onc3 (n=52 Kras/Hras/Rtl1 oncogene negative using 457 454T sequencing; n=42 Kras/Hras/Rtl1 oncogene positive using 454T sequencing) induced HCA 458 genomes.

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Trip12 16% Ovary 43% Rasa1 23% Ovary/Uterus 14% 16% Schwannoma Cul3 14%

Preputial Arid1b14%28%

Colon 14%

Crebbp 26% Ovary Ovary Ovary Uterus Schwannoma Preputial Colon Epc1 43% Epc1Ncoa2 43%33% Pten Pten 29% 29% Kmt2e 21% Nf1 Nf1 29% 29% 9% Apc ApcNcor229% 29%

Wac WacKmt2c29% 29%23%

Agfg1 29% Genetic AlterationAlteration No alterations AmplificationActivating DeepInactivating Deletion Akt3459 29%

Atxn1460 Figure 5: SB-driven gynecologic and other cancer histologies29% by cumulative tumor suppression. Birc6461 Recurrent inactivating SB insertions in29% Onc2.3-induced ovary, uterus, schwannoma, preputial gland, and

Cdc73462 colon tumors. 29%

Cep170 29%

Cntnap5a 29%

Fbxw7 29%

Fmnl2 29%

Gtf2e2 29%

Kcnt2 29%

Luc7l2 29%

Mark3 29%

Mgat5 29%

Nfib 29%

Plxdc2 43%

Rab2a 29%

Rfwd2 29%

Sgms1 29%

Sptbn1 29%

Zfand3 29%

Genetic Alteration Fusion Deep Deletion No alterations

Aiderus, Contreras, Meshey, et al., 2020 20

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Cul3Cul3 30.8%30.8% 8 8 Trip12Trip12 30.8%30.8% 8 8 Rasa1Rasa1 26.9%26.9% 7 7 Nek7Nek7 23.1%23.1% 6 6

Tnrc6bTnrc6b 19.2%19.2% 5 5 Rfwd2Rfwd2 19.2%19.2% 5 5 Zfand3Zfand3 19.2%19.2% 5 5

CmipCmip 15.4%15.4% 4 4 Mllt10Mllt10 15.4%15.4% 4 4 Atad2bAtad2b 15.4%15.4% 4 4 Med13lMed13l 15.4%15.4% 4 4 Ash1lAsh1l 15.4%15.4% 4 4 Caprin1Caprin1 15.4%15.4% 4 4 Ppp1r12aPpp1r12a 15.4%15.4% 4 4 Fgfr2Fgfr2 15.4%15.4% 4 4 Ptpn12Ptpn12 15.4%15.4% 4 4 PtenPten 15.4%15.4% 4 4

Zfp292Zfp292 15.4%15.4% 4 4 Brd4Brd4 15.4%15.4% 4 4 Atxn1Atxn1 15.4%15.4% 4 4 AdkAdk 15.4%15.4% 4 4

Dip2cDip2c 15.4%15.4% 4 4 Zfp148Zfp148 15.4%15.4% 4 4 Ube2wUbe2w 15.4%15.4% 4 4 463 Tnks2Tnks2 11.5%11.5% 3 3 464 Figure 6: SB-Onc2.3-Pan-TSG driver discovery . Recurrent inactivating SB insertions into trunk drivers

withIlf3 >99 reads from 3 or more Onc2.3Ilf3 11.5%11.5% -induced cancer 3genomes3 (n=27). SB-Onc2.3-Pan-TSG driver gene 465

SB insertion profiles are shown to the right. Literature References summarizing studies that provide in 466 Crlf3Crlf3 11.5%11.5% 3 3 467 vivo evidence for validation of the TSGs identified in this study (Supplementary Table 23). Source 468 image files CltcCltcmay be downloaded from11.5%11.5% figshare http://dx.doi.org/10.6084/m9.figshare.12816365 3 3 . Aox2Aox2 11.5%11.5% 3 3 Aiderus, Contreras, Meshey, et al., 2020 21

Luc7l2Luc7l2 11.5%11.5% 3 3

DgkdDgkd 11.5%11.5% 3 3 NamptNampt 11.5%11.5% 3 3 file:///Users/mannmb/Desktop/SB-Onc2.3file:///Users/mannmb/Desktop/SB-Onc2.3 paper paperdraft/fig draft/fig image/SB-GT image/SB-GT-all-n27sbcapseq_trunk100_driver_oncoprint-all-n27sbcapseq_trunk100_driver_oncoprint recolor recolor.html .html 1/3 1/3 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.17.254565; this version posted August 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

Novel TSGs not in CGC or TSGdb: Abl1, Abl2, Adam10, Akap11, Akap13, Ankrd11, App, Arid4a, Arid4b, Arih1, Arih2, Brd4, Calm1, Calm2, Cep170, Cep350, Ctnna1, Ctnnb1, Ehmt1, Ep400, Epc1, Gna11, Gna13, Gnai3, Gnaq, Gnb1, Itch, Jmjd1c, Kdm1a, Kdm2a, Kdm4c, Kdm5b, Kdm7a, Kmt2a, Kmt2e, Luc7l2, Luc7l3, Map2k2, Map4, Map4k3, Map4k4, Mapk1, Mapk14, Mapk1ip1l, Mapkapk2, Mark1, Mark2, Mark3, Med13l, Msi2, Ncoa2, Ncoa3, Pam, Rab1, Rab10, Rab11a, Rab29, Rab2a, Rab33b, Rab3gap1, Rab3gap2, Rab40c, Rab5c, Rab6a, Rabep1, Rabgef1, Rabif, Rac1, Rala, Ralb, Raly, Rbm33, Rere, Rock1, Rock2, Stk24, Stk35, Stk38, Stk40, Taok1, Taok3, Tjp1, Tram1, Tram2, Trip12, Ube2b, Ube2d2a, Ube2d3, Ube2e3, Ube2f, Ube2g1, Ube2h, Ube2i, Ube2n, Ube2o, Ube2q1, Ube2r2, Ube2w, Ube3a, Ube3c, Usp1, Usp34, Usp37, Usp40, Usp47, Usp48, Usp9x, Wac, Zfp292, Zmiz1, Zzz3 469

470 Figure 7: SB-Onc2.3-Pan-TSG driver enrichment with known TSGs datasets. The CGC TSG and TSGdb 471 datasets overlap with 167 of the SB-Onc2.3-Pan-TSG driver genes. 111 putative novel TSGs not in the CGC 472 TSG or TSGdb datasets, including validated TSGs (bold) described in the main text.

Aiderus, Contreras, Meshey, et al., 2020 22 a pT2/Onc2.3-MBM102 b

PvuI (42) T7 BamHI (201) F1 Ori TATA IR/DR(L) Lmut44 HindIII (496) 2.1 kb Wt

ApaLI (3689) XbaI (511) splice acceptor 0.98 kb Tg Linearization site ScaI (3502) ApaLI (595) PvuI (3392) exon pT2/Onc2.3-MBM102 Amp BamHI (711) 4395 bp ClaI (725) 4.4 kb SV40 PolyA XbaI (812) 2.3 kb 2.1 kb Wt 2.0 kb EcoRI (819) SV40 polyA 1.0 kb Tg En2 probe 5' primer ColE Ori T2/Onc2.3 geno 5.1 ApaLI (2443) KpnI (998) exon 32 T2/Onc2.3 geno3.2 Dra I digested gDNA Probe: En2-SA with P

HindIII (1190) Microinjection Summary: Inj#1515DS, Live born: 101, Tg positive: 56 (55%) En-2 SA

En2 probe 3'primer I I

T2/Onc3 3'geno primer Dra Dra IR/DR(R) Rmut13,Æ130,143,150 TATA SA En2-SA SB-T2/SB-GT (Onc2.3) (pT2/Onc2.3-MBM102) BamHI (1694) XhoI (1716) T3 Detected element sizes (En2-SA probe) KpnI (1735) En2 endogenous 2.1 kb 473 LacZ promoter pT2/Onc2.3 monomers 1.0 kb

474 Supplementary Figure 1: Transgenic SB-T2/Onc2.3 founder mice. (a) Plasmid map of pT2/Onc2.3- 475 MBM102, denoting essential features and position in parenthesis, used to create the T2/Onc2.3 Wednesday, November 01, 2006 2:49:37 PM Page 1 476 high-copy transgenic lines. (b) Southern blot of T2/Onc2.3 founder mice using a probe corresponding to 477 the En2-SA (Engrailed 2 splice acceptor) element within the SB-T2/SB-GT allele construct that also cross 478 hybridizes to the endogenous En2 mouse gene on 5. Genomic DNA digested to completion 479 with DraI restriction enzyme and detected with a radioisotope-32P labeled En2-SA probe identifies the 480 diploid endogenous En2 locus as a discrete 2.1 kb band and any all copies of the T2/SB-GT monomer that 481 have been liberated from the their randomly inserted transgenic loci as a discrete 1.0 kb band. Mice with 482 multi-copy concatemer alleles are identified as containing darker staining bands relative to the two copies 483 of the En2 endogenous locus band. Blue arrows and dotted boxes denote animals selected for germ line 484 breeding — five separate transgenic founders, three females (TG.14885, TG.14922, and TG.14942) and 485 two males (TG.14913 and TG.14927), were selected for mating with wildtype C57BL/6J mice to confirm 486 the germ line transmission of the SB-T/2SB-GT concatemer alleles to progeny. Mice denoted with blue 487 dotted boxes produced transgenic carrier pups with a transgene copy numbers that differed between 488 individuals, suggesting the presence of two or more independent transgenic concatemer integration sites. 489 Mice denoted with red dotted boxes produced transgenic carrier pups with a transgene copy number that 490 did not differ between individuals, suggesting that they resulted from a single transgenic concatemer 491 integration site. Lines established from founders TG.14913, TG.14922, and TG.14942 were expanded and 492 bred for further experiments. BamHI restriction digested lambda (ƛ)-phage DNA is provided as a 493 reference, a small amount was added to the radioisotope-32P labeling reaction with the En2-SA probe to 494 show detection on the developed Southern blot.

Aiderus, Contreras, Meshey, et al., 2020 23 a +

bp III Hind : λ M: 100 M: Onc2.3(TG.14913) Onc2.3(TG.14942) Onc2.3(TG.14922) Onc3(TG.12740) Onc2(TG.6070) Onc2 (TG.6113) Onc2(TG.6113) I I Dra Dra

SA En2-SA Onc2.3

Predicted Sizes (En2 probe) En2 2.1 kb pT2/Onc2 1.7 kb pT2/Onc3 1.6 kb pT2/Onc2.3 1.0 kb

b

En2 @ 2.1 kb (diploid) Onc3 @ 1.7 kb Onc2 @ 1.6 kb

Onc2.3 @ 1.0 kb

495

496 Supplementary Figure 2: Estimating SB transposon concatemer copy number from different SB 497 strains. (a) Inverse image of EtBr stained agarose gel (1.2% TBE, run at 30 volts for 30 hours) containing 498 genomic DNA digested with Dra I for 16 hours at 37 ºC for Southern blot analysis. Molecular weight 499 markers: left, lambda cut with Hin DIII; right, 100 bp ladder. (b) Southern blot demonstrating relative 500 concatemer copy number differences between high-copy and low-copy SB transposon alleles in 501 homozygous mice with unmobilized transposons. The En2 site provides a reference for a single copy, 502 diploid gene.

Aiderus, Contreras, Meshey, et al., 2020 24 a +

bp III Hind : λ M: 100 M: Onc2.3(TG.14913) Onc2.3(TG.14942) Onc2.3(TG.14922) Onc3(TG.12740) Onc2(TG.6070) Onc2 (TG.6113) Onc2(TG.6113) HI HI Bam Bam

SA En2-SA Onc2.3

Predicted Sizes (En2 probe) En2 9.9 kb pT2/Onc2 1.6 kb pT2/Onc3 1.7 kb pT2/Onc2.3 1.0 kb

b Onc2.3(Tg.14913) Onc2.3(TG.14942) Onc2.3(TG.14922) Onc3(TG.12740) Onc2(TG.6070) Onc2 (TG.6113) Onc2(TG.6113) En2 @ 9.9 kb (diploid)

Onc3 @ 1.7 kb Onc2 @ 1.6 kb

Onc2.3 @ 1.0 kb 503

504 Supplementary Figure 3: Estimating SB transposon concatemer copy number from different SB 505 strains. (a) Inverse image of EtBr stained agarose gel (1.2% TBE, run at 30 volts for 30 hours) containing 506 genomic DNA digested with BamHI for 16 hours at 37 ºC for Southern blot analysis. Molecular weight 507 markers: left, lambda cut with BamHI; right, 100 bp ladder. (b) Southern blot demonstrating relative 508 concatemer copy number differences between high-copy and low-copy SB transposon alleles in 509 homozygous mice with unmobilized transposons. The En2 site provides a reference for a single copy gene.

Aiderus, Contreras, Meshey, et al., 2020 25 a b Heterozygous Homozygous All SB-Onc2.3 alleles combined Tg.SB-Onc2.3 Rosa26SBase/SBase Observed Expected

X Single Heterozygous 148 (78%) 94.5 controls (Rosa26SBase/+)

Double Heterozygous carriers 41 (22%) 94.5 (Tg.SB-Onc2.3; ½ Single Heterozygous ½ Double Heterozygous Rosa26SBase/+) Rosa26SBase/+ Tg.SB-Onc2.3;Rosa26SBase/+ !2=60.557 Total 189 P<0.001

c SB-Onc2.3 allele TG.14922 TG.14942 TG.14913

Observed Expected Observed Expected Observed Expected

Single Heterozygous controls (Rosa26SBase/+) 37 (90%) 20.5 51 (72%) 35.5 60 (78%) 38.5

Double Heterozygous carriers (Tg.SB-Onc2.3; Rosa26SBase/+) 4 (10%) 20.5 20 (28%) 35.5 17 (22%) 38.5

!2=25.561 !2=13.535 !2=24.013 Total 41 P<0.001 71 P<0.001 77 P<0.001

d – + + + + + + Rosa26SBase11 + + + – + + – T2/Onc2.3 (Tg.14922) En2 single copy gene cut | En2-SA probe En2-SA | cut

HI Unmobilized pT2/Onc2.3

Bam @ donor site

Tail Newborn e 510

511 Supplementary Figure 4: Embryonic lethality in double heterozygous mice. (a) Mouse cross to 512 generate singe allele control and double allele experimental mice. (b) Less than expected number of 513 progeny resulted from matings between double heterozygous carrier mice resulting from crosses 514 between SB T2/Onc2.3 and constitutive SBase expression. (c) Onc2.3 (Tg/+); SB’B’ (neo/+) double hets 515 are not born in the expected Mendelian frequencies, Goodness of Fit test values provided. (d) SB 516 transposition and genome mobilization of T2/Onc2.3 allele in vivo by constitutive SBase expression in 517 compound double heterozygous carriers. Southern blot demonstrating change in T2/Onc2.3 (Tg.14922) 518 allele donor site concatemer copy number of in single carrier mice with unmobilized transposons (left 519 lane) and significant depletion in double carrier mice from tail biopsies of wean pups or from whole body 520 newborn kidney specimen. (e) Modified SB excision PCR(Mann et al., 2015) demonstrating transposition 521 of the T2/Onc2.3 (Tg.14922) allele in vivo from routine tail biopsies taken from weaned mice for 522 genotyping. Presence of the SB excision PCR product infers SB transposon and SB transposase alleles are 523 all present within the germ line of the weaned mouse.

Aiderus, Contreras, Meshey, et al., 2020 26 a Onc2.3 double homozygous Onc2.3 double homozygous Tg.12922 / Tg.14922; Tg.14942 / Tg.14942; LSLSBase/LSLSBase Actb-Cre homozygous LSLSBase/LSLSBase Tg.Actb-Cre/Tg.Actb-Cre

X X Control Parental SB-Onc2.3 Littermates SB-Onc2.3-TG.12922 SBCapSeq SB-Onc2.3-TG.12942 Tumors 6 – skin 6 – lung 6 – liver 9 – other b 100

P=0.0015 75 Log-rank test (Mantel-Cox)

50

Tumor-free survival (%) survival Tumor-free 25

Actb-cre | Onc2.3–TG.14942 | LSLSBase (n=58) Actb-cre | Onc2.3–TG.14922 | LSLSBase (n=49) 0 0 50 100 150 200 250 300 350 400 450 500 550 600 Age (d)

c 100

P=0.0033 75 Log-rank test (Mantel-Cox)

50

Tumor-free survival (%) survival Tumor-free 25 Actb-cre | Onc2.3 (n=23) Actb-cre | Onc2.3 | LSLSBase (n=107) 0 0 50 100 150 200 250 300 350 400 450 500 550 600 Age (d) 524

525 Supplementary Figure 5: Overview of SB-induced tumor studies. (a) SB-Onc2.3 breeding strategy and 526 genotype cohorts aged to generate the SB100 -Onc2.3 experimental and control cohorts of mice used in this 527 study. (b) Kaplan-Meier survival plots comparing SB-Onc2.3 cohorts (Mantel-Cox log-rank test, P = P<0.0001 75 Log-rank test 528 0.0015). (c) Kaplan-Meier survival plots comparing the combined SB(Mantel-Cox)-Onc2.3 experimental and control 529 cohorts (Mantel-Cox log-rank test, P = 0.0033). 50

Tumor-free survival (%) survival Tumor-free LSL 25 Actb-cre | Onc2 | SBase (n=78) Actb-cre | Onc3 | LSLSBase (n=87) Actb-cre | Onc2.3 | LSLSBase (n=107)

0 Aiderus, Contreras, Meshey,0 50 et100 al.,150 2020200 250 300 350 400 450 500 550 600 27 Age (d) a b

c d

e f

g h

530

531 Supplementary Figure 6: Necropsy and histological analysis of SB-Onc2.3 tumors. (a-b) Necropsy 532 image of lung tumors: (a) white mass (adenocarcinoma) from right apical lobe and (b) small white nodule 533 at bottom (adenoma) and at top of lung - large white mass with red area (adenocarcinoma) from the right 534 ventral lobe. Histology and tumor classification from sections of lung masses stained with hematoxylin 535 and eosin (H&E): (c-d) Lung adenoma (40×), with inset showing carcinoma differentiation in (d) (200×) 536 and Lung (e-h) adenocarcinoma areas 200X, (e) carcinoma (200×), (f) adenocarcinoma (200×), and (g) 537 sarcoma (200×). Source image files and additional histology images may be downloaded from figshare 538 http://dx.doi.org/10.6084/m9.figshare.12816305.

Aiderus, Contreras, Meshey, et al., 2020 28 a b

c d

e f

539

540 Supplementary Figure 7: Evaluating the reproducibility of SBCapSeq from bulk SB-Onc2.3 tumors. 541 Representative plots of the individual SB insertion sites based on read depth from (a) cuSCC, (b) HCA, (c) 542 LUAA, (d) Ovarian adenocarcinoma, (e) Schwannoma, and (f) astrocytoma genomes from genomic DNAs 543 created from bulk tumor specimens from technical replicate libraries (independent library sequencing 544 runs applied to the same biological specimen isolate) comparing library run 1 (x-axis) to library run 2 (y- 545 axis). Biological reproducibility of the cuSCC, HCA, LUAA, ovarian adenocarcinoma, and Schwannoma 546 specimen libraries is high, supported by both Pearson’s and Spearman’s correlation metrics, and 547 identifies the all of SB insertion sites with read depths of 20 or higher (a-e). In contrast, technical 548 reproducibility of the astrocytoma specimen libraries is exceptionally low and fails to identify any read 549 depth insertion sites higher than 22 reads (e), indicating that the insertions are likely background 550 passenger insertion events that are not clonally selected during astrocytoma progression.

Aiderus, Contreras, Meshey, et al., 2020 29 a SB-Rasgrf1 fusion cDNA transcript ! Onc3-SD|Rasgrf1 ex9 cDNA! ------∨------! CTCAGGT|GATCATGCATGACGŸŸŸ! ŸŸŸ SA CAG SD En2-SA -M--H--D-- ! SB|Rasgrf1ΔN ! SV40-polyA

CAG SD Exon 9

ΔN426 RASGRF1 PH2 Ras- Ras- 836 aa GEF1 GEF2

FL Ras- Ras- RASGRF1 PH1 IQ DH PH2 1,262 aa GEF1 GEF2 b

551

552 Supplementary Figure 8: Activating SB insertions into the Rasgrf1 locus drive overexpression an 553 oncogenic delta-N isoform. (a) Recurrent activating SB insertions in Onc3-induced lung cancer genomes 554 drives expression of an N truncated RASGRF1∆N426 isoform that lacks the first 426 amino acids in the full 555 length RASGRF1 protein. The protein domains for RASGRF1 from UniProt 556 (http://www.uniprot.org/uniprot/P27671): PH1 (aa 22 – 130 in the full length), IQ (aa 208 – 233 in the 557 full length), and DH (aa 244 – 430 in the full length) absent in the predicted RASGRF1ΔN426 oncoprotein; 558 PH2 (aa 460 – 588 in the full length), Ras-GEF1 (aa 635 – 749 in the full length) and Ras-GEF2 (aa 1027 – 559 1259 in the full length) present in the predicted RASGRF1ΔN426 oncoprotein. (b) Expression of the delta-N 560 RASGRF1 is positively correlated with SBCapSeq read depth (Pearson r=0.9761; Spearman r=0.9848; 561 P<0.0001; Supplementary Table 24).

Aiderus, Contreras, Meshey, et al., 2020 30 6/16/2020 SB%7CP53%7CLung-454-SB Drivers-oncoprint.svg

Trp53 mice 100%

Rasgrf1 28%

Ptprd 48%

Rbms3 34%

Dopey1 34%

Astn2 28%

Trip12 24%

Nfia 24%

Ube2cbp 24%

Rngtt 21%

Stag1 21%

Setd2 21%

Rdx 21%

Tnr 21%

Rabgap1l 21%

Nf1 17%

Tcf12 17%

Arhgap42 17%

Fam214a 17%

Rfwd2 17%

Pde4b 17%

Mbnl1 17%

Rfx7 17%

Cdk5rap2 17%

Genetic Alteration Trp53 WT Trp53 KO/+ Trp53 R172H/+ Activating Inactivating No alterations 562

563 Supplementary Figure 9: Landscape of candidate trunk drivers mutated in SB-induced LUAA with 564 Splink_454T sequencing. SB Driver Analysis applied to Splink_454 SB insertion data (Supplementary 565 Table 8) with read depth cutoff of 6 on 29 late-stage HCA genomes. FWER-corrected significant driver 566 genes (rows) were sorted by occurrence within the cohort genomes (columns).

file:///Users/mannmb/Desktop/SB%7CP53%7CLung-454-SB Drivers/SB%7CP53%7CLung-454-SB Drivers-oncoprint.svg 1/1

Aiderus, Contreras, Meshey, et al., 2020 31 Gphn 32.6% Nfia 30.5% Vps13b 29.5% Foxp1 28.4% Rian 26.3% Fndc3b 26.3% Ghr 26.3% Arid1b 26.3% Akap13 24.2% Crebbp 23.2% Rere 23.2% Fchsd2 23.2% Stag2 21.1% Ccny 21.1% Trip12 20.0% Itpr1 20.0% Kras 20.0% Zhx3 18.9% Tnks 18.9% Cul3 18.9% Hras 18.9% Nfat5 16.8% Itch 16.8% Fto 15.8% Mir1195 15.8% Ube2g1 14.7% Ankrd11 14.7% Kat6a 14.7% Raf1 13.7% Nr3c1 12.6% Mkln1 12.6% Patl1 11.6% Vti1a 11.6% Efna5 8.4% Elf1 8.4% Pex14 8.4% Gprin3 6.3% Cnot2 6.3% Mir3071 0.0%

NIB Trp53 genotype

Sense strand, high reads Sense strand, low reads An2-sense strand, high reads An2-sense strand, low reads

SB Ac2va2on pa8ern SB Indeterminate pa8ern SB Inac2va2on pa8ern

567 Trp53 R172H/+ Trp53 KO/+

568 Supplementary Figure 10: Landscape of candidate trunk drivers mutated in SB-induced HCA with 569 Splink_454T sequencing. SB Driver Analysis applied to Splink_454 SB insertion data (Supplementary 570 Tables 10-12) with read depth cutoff of 6 on 95 late-stage HCA genomes. FWER-corrected significant 571 driver genes (rows) were sorted by occurrence within the cohort genomes (columns). Waterfall plots 572 were generated on all insertions, and insertion patterns determined by progression driver analysis are 573 shown to the side. NIB, normalized insertion burden from lowest (light gray) to highest (black). Trp53 574 genotype shown from Trp53 +/+ (light blue), Trp53 R172H/+ (blue) and Trp53 KO/+ (dark blue).

Aiderus, Contreras, Meshey, et al., 2020 32 575 METHODS

576 Generation of pT2/Onc2.3 vector. SB transposon vector pT2/Onc2(Dupuy et al., 2005) (a gift from A. 577 Dupuy) was sequentially digested with restriction enzymes XmaI (NEB), at position 717 bp, and EcoRI 578 (NEB) at position 729 bp, at 37 ºC for 30 m each, per manufacturer’s suggested protocol, to linearize the 579 plasmid. Linear plasmid was visually confirmed as an ~4.9 kb on a 1% agarose TAE gel stained with EtBr 580 viewed under UV light. A small piece of agarose gel containing the linear pT2/Onc2 was excised, purified 581 using GFX columns (Amersham Biosciences #414581), and saved for ligation. A PCR cloning strategy was 582 used to insert an extra bi-directional SV40-polyA termination sequence into the pT2/Onc2 vector. Using 583 100 uM each of two complimentary overlapping (bold) oligos, XmaI+ClaI.SV40-pA 5’-ATG CAT GCA TCC 584 CGG GCA TCG ATG CAG TGA AAA AAA TGC TTT ATT TGT GAA ATT TGT GAT GCT ATT GCT TTA TTT 585 GTA ACC-3’ and SV40-pA.EcoRI+XbaI 5’-ATG CAT GCA TGA ATT CGT CTA GAA ACT TGT TTA TTG CAG 586 CTT ATA ATG GTT ACA AAT AAA GCA ATA GCA TCA C-3’ and PCR SuperMix Taq (Invitrogen 587 #10572014), we amplified a 128 bp fragment (5’-ATG CAT GCA TCC CGG GCA TCG ATG CAG TGA AAA 588 AAA TGC TTT ATT TGT GAA ATT TGT GAT GCT ATT GCT TTA TTT GTA ACC ATT ATA AGC TGC AAT AAA 589 CAA GTT TCT AGA CGA ATT CAT GCA TGC AT-3’) using at thermal cycler program: template denaturation 590 at 94ºC for 90 s followed by 30 cycles of 94ºC for 30 s, 50ºC for 45 s, and 72ºC for 45 s followed by 72ºC 591 for 300 s and cooled to 4ºC. PCR product was visually confirmed by running the PCR product on a 2% 592 agarose TBE gel stained with EtBr viewed under UV light. A small piece of gel containing the linear PCR 593 product was excised, purified using GFX columns (Amersham Biosciences #414581), and used to ligate 594 into pGEM®-T Easy Vector System (Promega #A1360) at room temperature for 60 m using the 595 manufacturer’s suggested protocol. Ligation products were electroporated into MAX efficiency DH10B 596 competent cells (Invitrogen #18297010), plated on LB agar plates with ampicillin, and incubated 37 ºC 597 for 18 hrs. Miniprep DNA from selected transformants was sequentially digested with XmaI (NEB) and 598 EcoRI (NEB), at 37 ºC for 30 m each, per manufacturer’s suggested protocol. The ligation product was run 599 on a 2% agarose TBE gel stained with EtBr viewed under UV light, and a small piece of gel containing the 600 108 bp fragment was excised, purified using GFX columns (Amersham Biosciences #414581) prior to 601 ligation. Finally, a ligation reaction using a 1:5 ratio of pT2/Onc2:XmaI-EcoRI linear vector and SV40- 602 polyA: :XmaI-EcoRI insert, respectively, was performed using T4 DNA Ligase at room temperature for 30 603 m, followed by heat inactivation at 65 ºC for 20 m. Ligation products were electroporated into MAX 604 efficiency DH10B competent cells (Invitrogen #18297010), plated on LB agar plates with ampicillin, and 605 incubated at 37 ºC for 18 hrs. Miniprep DNA from selected transformants was digested with HindIII 606 (NEB), at 37 ºC for 60 m each, per manufacturer’s suggested protocol. Recombinant pT2/Onc2.2 vector 607 was identified by the presence of three fragments at 3.658 kb, 0.8 kb, and 0.6 kb fragments. pT2/Onc2.2 608 vector DNA was cut with restriction enzyme AscI (NEB #R0558S), at 37 ºC for 60 m, to linearize the 609 plasmid. Linear plasmid was visually confirmed on a 1% agarose TAE gel stained with EtBr viewed under 610 UV light. A small piece of agarose gel containing the linear pT2/Onc2.2 vector was excised and purified 611 using GFX columns (Amersham Biosciences #414581). PCR amplification was performed using 100 ng of 612 the purified linearized pT2-Onc2.2 vector template and a pair of oligos T2/Onc2.f1 5'-ATG CGA ATT CAA 613 CGC GCG TTA AGA TAC ATT GA-3' engineered to contain an EcoRI site (underlined) and T2/Onc2.r1 5'- 614 ATC TAT GGC TCG TAC TCT ATA GGC-3' designed to amplify the pT2/Onc2 vector excluding the MSCV 5’ 615 LTR minimal promoter and Lun-SD sequences using platinum Hi-Fi DNA Taq polymerase (Invitrogen 616 #11304-028) in 1X Hi-Fi PCR buffer (Invitrogen #52045) supplemented with 2 uL of 50 mM MgSO4 and 617 dNTPs (Roche#11-581-295-001) and thermal cycler program: template denaturation at 95ºC for 90 s 618 followed by 30 cycles of 95ºC for 45 s, 55ºC for 60 s, and 72ºC for 270 s followed by 72ºC for 600 s and

Aiderus, Contreras, Meshey, et al., 2020 33 619 cooled to 37ºC. Then, 1 unit of restriction enzyme DpnI (NEB #R0176S) was added (to digest the 620 methylated plasmid from vector template grown in and enrich PCR amplified template during 621 ligation) to each PCR tube and incubated at 37ºC for 30 m, followed by heat inactivation at 80ºC for 20 m, 622 and then cooled to 4 ºC. The PCR product was column purified, resuspended in ddH2O, and digested with 623 EcoRI (NEB) at 37 ºC for 60 m (one EcoRI site was added by the oligo and the other occurs within the 624 pT2/Onc2.2 vector at position 819). Gel and column purified pT2/Onc2.3 linear vector (4.395 kb) was 625 self-ligated using T4 DNA ligase at room temperature for 30 m, followed by heat inactivation at 65 ºC for 626 20 m. Ligation products were electroporated into MAX efficiency DH10B competent cells, plated on LB 627 agar plates with ampicillin, and incubated at 37 ºC for 18 hrs. Miniprep DNA from selected transformants 628 was digested with HindIII (NEB), at 37ºC for 60 m each, per manufacturer’s suggested protocol. 629 Recombinant pT2/Onc2.3 vector (Supplementary Figure 1a) was identified by the presence of two 630 fragments at 3.701 kb and 0.694 kb fragments. Cloning maps and sequence files may be downloaded from 631 figshare http://dx.doi.org/10.6084/m9.figshare.12816452. Several pT2/Onc2.3 vector clones were 632 sequenced using BigDye® direct cycle sequencing kit, using the manufacturer’s suggested protocol, and 633 the following primers: T7, 5'-GTAATACGACTCACTATAGGG-3'; T2/Onc.sp5.1, 5'- 634 GACTGTGCCTTTAAACAGCTTGG-3'; T2/Onc.sp5.2, 5'-TCCTGTGCCAGACTCTGGCGC-3'; and T2/Onc.sp5.3, 635 5'-GGGTGGTGATATAAACTTGAGGCTG-3'. A single pT2/Onc2.3 clone with full sequence identity to the 636 vector map was re-electroporated into MAX efficiency DH10B competent cells (Invitrogen #18297010), 637 plated on LB agar plates with ampicillin, and incubated at 37ºC for 18 hrs.

638 Generation of T2/Onc2.3 transgenic mice. pT2/Onc2.3 DNA was linearized with restriction enzyme 639 with ScaI (NEB #R3122) at position 3,502 bp (Supplementary Figure 1a) at 37ºC for 90 m, followed by 640 heat inactivation at 80 ºC for 20 m. pT2/Onc2.3:ScaI linear plasmid, at 2 ng/uL, 4 ng/uL and 10 ng/uL, 641 was prepared for microinjection into (B6C3)F2 hybrid embryos using standard techniques (Dupuy et al., 642 2005). Tail biopsy genomic DNA from founder animals was digested with DraI (NEB) and BamHI (NEB), 643 run on a 0.8% TAE agarose gel at 30 v for 16 h, transferred to membrane, and screened by Southern 644 blotting using a 32P-labeled En2-SA (splice acceptor) probe, a 500 bp En2-SA PCR product with 645 pT2/Onc2.3 template and primers T2.3-En2.5Probe, 5'-GCTGCAATAAACAAGTTGGCCG-3' and T2.3- 646 En2.3Probe, 5'-CTTGGGTCAAACATTTCGAGTAGCC-3’, and standard methods. Individual transgenic lines 647 (n=5) were established by backcrossing founders to C57BL/6J (JAX#000664). Germ line transmission 648 was confirmed by Southern blotting using standard techniques. All five lines transmitted to offspring, but 649 only three lines, T2/Onc2.3(TG.14913) (TgTn(sb-T2/Onc2.3)14913Mbm), T2/Onc2.3(TG.14922) 650 (TgTn(sb-T2/Onc2.3)14922Mbm), and T2/Onc2.3(TG.14942) (TgTn(sb-T2/Onc2.3)14942Mbm), 651 segregated a transposon concatemer as a single, discreet locus by Southern blot genotyping. Subsequent 652 offspring were genotyped by multi-plex PCR using primers specific to the SB transposon T2.3-sense, 5'- 653 CTG TCA GGT ACC TGT TGG TCT GAA AC-3' and T2.3-antisense, 5'-CCT CAA GCT TGG GTG CGT G-3', which 654 yields a 370 bp PCR product, and control primers Actb-sense, 5'-ACA AGG TCA AAA CTC AGC AAC AAG T- 655 3' and Actb-antisense, 5'-GCT GAG AGG GAA ATT GTT CAT TAC A-3', which yields a 700 bp PCR product. 656 Multiplex PCR genotyping protocol for SB-Onc2.3 mice may be downloaded from figshare 657 http://dx.doi.org/10.6084/m9.figshare.12811301.

658 The following alleles were used to construct the SB-driven mouse model of multiple solid tumor 659 histologies: Actb-Cre (FVB/N-Tg(ACTB-cre)2Mrt/J, ref. (Lewandoski et al., 1997));Trp53flox/+ (FVB.129P2- 660 Trp53tm1Brn/Nci, ref. (Jonkers et al., 2001)); Trp53LSL-R172H/+ (129S4-Trp53tm2Tyj/Nci; ref. (Olive et al., 2004)); 661 T2/Onc2(TG.12740) (TgTn(sb-T2/Onc3)12740Njen; ref. (Dupuy et al., 2009)); and Rosa26-LSL SBase or 662 SBaseLSL; (Gt(ROSA)26Sortm2(sb11)Njen; ref. (Starr et al., 2009)). The resulting cohorts of mice were on mixed

Aiderus, Contreras, Meshey, et al., 2020 34 663 genetic backgrounds consisting of C57BL/6J, 129, C3H and FVB. Genotyping by PCR assays with primers 664 specific to the alleles was performed. No sample size estimate was used. The production and 665 characterization of all SB and SBase mouse strains was supported by the Department of Health and 666 Human Services, National Institutes of Health and the National Cancer Institute. Mice were bred and 667 maintained in accordance with approved procedures directed by the respective Institutional Animal Care 668 and Use Committees in the National Cancer Institute Frederick National Lab, A*STAR Biological Resource 669 Centre, and H. Lee Moffitt Cancer Center and Research Institute/University of South Florida. Gross 670 necropsies were performed and all masses were documented and prepared for subsequent analysis. Both 671 sexes were used for experiments, including reporting of cohort data survival analysis. No randomization 672 or blinding was performed, all mice were assigned to groups based on genotype.

673 Histological analysis. Histological analysis of necropsy tissues was performed on 5-μm sections of 674 formalin-fixed, paraffin-embedded (FFPE) samples stained with hematoxylin and eosin (H&E). Nuclear 675 staining of SB transposase (SBase) was confirmed by immunohistochemistry on FFPE tissues after 676 antigen retrieval (pH 9) and endogenous peroxidase inhibition followed by overnight incubation with 677 mouse to SBase (anti-SBase; R&D Systems; pH 9; 1:200 dilution), followed by incubation with 678 primary antibody, chromogen detection (with HRP polymer, anti-rabbit or anti-mouse, with Envision 679 System from Dako) and hematoxylin counterstaining were performed per manufacturer’s instructions. 680 Genomic DNA (gDNA) was isolated from flash frozen or FFPE necropsy specimens using Qiagen Gentra® 681 Puregene® DNA isolation kit protocol for tissue using the manufacturer’s protocol (see Supplementary 682 Note 2).

683 Mapping SB insertion sites. Full details for the SBCapSeq protocol, an enhanced SBCapSeq method 684 optimized for sequencing from solid tumors (Mann et al., 2019), will be published elsewhere (Mann, 685 Mann et al., in preparation; for general protocol and concept, see also refs. (Mann et al., 2016a; Mann et 686 al., 2016b)). Briefly, for selective SB insertion site sequencing by liquid hybridization capture, gDNA (0.5 687 µg per sample) of bulk tumor genomes was used for library construction using the AB Library Builder™ 688 System, including random fragmentation and ligation of barcoded Ion Xpress™ sequencing adapters. 689 Adapter-ligated templates were purified by Agencourt® AMPure beads® and fragments with insert size of 690 ~200 bp were excised, purified by Agencourt® AMPure® beads, amplified by 8 cycles of adapter-ligation- 691 mediated polymerase chain reaction (aLM-PCR), and purified by Agencourt® AMPure® beads with elution 692 in 50 µl of TE (1X Tris- Ethylenediaminetetraacetic acid [EDTA], pH8). Capture hybridization of single or 693 multiplexed up to 12 barcoded libraries (60 ng per sample) was performed using custom xGen® 694 Lockdown® Probes (IDT; full details available at https://doi.org/10.35092/yhjc.11441001.v1). All 120- 695 mer capture and blocking oligonucleotide probes were purchased from IDT as Ultramer DNA Oligos with 696 Standard Desalting. Captured library fragments were further amplified by 12 cycles of aLM-PCR and run 697 using an Agilent 2100 Bioanalyzer or TapeStation to estimate enrichment. Captured libraries were 698 quantified by Qubit® Fluorometer and quantitative Real Time-PCR (qRT-PCR) were used to dilute 699 libraries for template preparation and Ion Sphere™ Particle (ISP) loading using Ion Chef™ System and

700 sequencing on the Ion Proton™ platform with PIv3 semiconductor wafer chips per manufacturers 701 recommended instructions. High-throughput sequencing of up to 39 multiplex captured libraries was 702 carried out per PIv3 chip to achieve an average of 4.5 million reads per barcode. Reads containing the 703 transposon IRDR element were processed using the SBCapSeq bioinformatic workflow as 704 described(Mann et al., 2016b). For splink_454 sequencing (see Supplementary Note 3), SB insertion 705 reads were generated by 454 GS Titanium sequencing (Roche) of pooled splinkerette PCR reactions with

Aiderus, Contreras, Meshey, et al., 2020 35 706 nested, barcoded primers was performed as described previously (Mann et al., 2012; Mann et al., 2015; 707 March et al., 2011). Pre- and post-processing of 454 reads to assign sample DNA barcodes, filter out local 708 hopping events from donor , and map and orient the SB insertion sites across the entire 709 nuclear genome of the mouse was performed. Donor chromosomes SB insertions were filtered away prior 710 to identification of common insertion sites using SB Driver Analysis (Newberg et al., 2018a).

711 SB Driver Analysis Discovery, Progression and Trunk Drivers. Using the SB Driver Analysis framework 712 (Newberg et al., 2018a), Discovery significant progression drivers are defined as statistically significant 713 recurrently altered genes using False Discovery Rate (FDR; Benjamini–Hochberg procedure) multiple 714 hypothesis testing P-value correction and Genome significant progression drivers are defined as 715 statistically significant recurrently altered genes using Family Wise Error Rate (FWER; Holm–Bonferroni 716 procedure) multiple hypothesis testing P-value correction from all SB insertion events within a dataset 717 (no read depth filtering) to capture the widest possible list of potential driver genes. In contrast, Genome 718 significant trunk drivers are defined as statistically significant recurrently altered genes using FWER 719 multiple hypothesis testing P-value correction from SB insertion events with a pre-determined minimum 720 read depth filtering of the dataset to report a statistically stringent prioritized driver gene list. Trunk 721 drivers have the highest probability to be represented recurrently across tumors with the highest read 722 depths, suggesting early and/or highly selected insertion events during bulk tumor growth. As a rule, 723 Progression Drivers are a subset of Discovery Drivers and Trunk Drivers are often also Progression 724 and/or Discovery Drivers (Newberg et al., 2018a). The BED files containing all SB insertions from 725 histologically verified SB-Onc2.3 tumor specimens were filtered to consider only insertions represented 726 by 100 or more reads in three or more tumors. When genes from a specimen genome were found to 727 contain >1 SB insertion in the same RefSeq gene, only the SB insertion with the highest sequence read 728 count was used for SB Driver Analysis calculations. SB Driver Analysis (Newberg et al., 2018a) was 729 performed to identify the genes significantly enriched for insertions at high read counts with a FWER- 730 corrected P<0.05 were termed trunk driver genes based on the inferred high clonality across the tumor 731 population (Newberg et al., 2018a).

732 qRT-PCR. Total RNA was purified and DNase treated using the RNeasy Mini Kit (Qiagen). Synthesis of 733 cDNA was performed using SuperScript VILO Master Mix (Life Technologies). Quantitative PCR analysis 734 was performed on the QuantStudio 12K Flex System (Life Technologies) or 7900HT Sequence Detection 735 System (Applied Biosystem). All signals were normalized to the levels of GAPDH TaqMan probes. TaqMan 736 probes were obtained from Life Technologies.

737 Software. Unless otherwise noted, bioinformatic analysis pipelines, report generation, and figure 738 visualization performed using bash, R, Python scripts, Vector NTI, and GraphPad Prism 8 software 739 (Version 8.1.1).

740 URLs. TgTn(sb-T2/Onc2.3) 14942Mbm, http://www.informatics.jax.org/allele/MGI:6441755; TgTn(sb- 741 T2/Onc2.3)14922Mbm, http://www.informatics.jax.org/allele/MGI:6441757; TgTn(sb- 742 T2/Onc2.3)14913Mbm, http://www.informatics.jax.org/allele/MGI:6441760; Mouse Genome 743 Informatics (MGI) database, http://www.informatics.jax.org/; Gt(ROSA)26Sortm2(sb11)Njen, 744 http://www.informatics.jax.org/allele/MGI:3839796; FVB/N-Tg(ACTB-cre)2Mrt/J, 745 https://www.jax.org/strain/003376; FVB.129P2-Trp53tm1Brn, https://www.jax.org/strain/008462; 746 129S4-Trp53tm2Tyj, https://www.jax.org/strain/002101; Enrichr,

Aiderus, Contreras, Meshey, et al., 2020 36 747 http://amp.pharm.mssm.edu/Enrichr/; Tumor Suppressor Gene Database, 748 https://bioinfo.uth.edu/TSGene/; UniProt, http://www.uniprot.org/; COSMIC Cancer Gene Census, 749 https://cancer.sanger.ac.uk/census/; VENNY 2.1, https://bioinfogp.cnb.csic.es/tools/venny/; 750 Oncoprinter, http://www.cbioportal.org/oncoprinter.

751 Supplementary Notes: Supplementary Notes 1–3 may be downloaded from figshare 752 http://dx.doi.org/10.6084/m9.figshare.12811979.

753 Supplementary Tables. Supplementary Table datasets may be downloaded from figshare 754 http://dx.doi.org/10.6084/m9.figshare.12811772. Brief descriptions of each table are provided for 755 reference.

756 Supplementary Table 1: Tumor incidence and subgroup classifications by cohort groups

757 Supplementary Table 2: Sequencing projects summary by cohort

758 Supplementary Table 3: Specimen metafile data for projects sequenced using SBCapSeq protocol 759 with Ion Torrent Proton sequencer

760 Supplementary Table 4: BED file of SB insertions for Skin-Onc2.3_SBC cohort

761 Supplementary Table 5: BED file of SB insertions for Lung-Onc2.3_SBC cohort

762 Supplementary Table 6: BED file of SB insertions for Lung-Onc3_SBC cohort

763 Supplementary Table 7: Specimen metafile data for projects sequenced using Splink_PCR 764 protocol with 454 GS-FLX Titanium pyrosequencer

765 Supplementary Table 8: BED file of SB insertions for Lung29_454

766 Supplementary Table 9: SB Driver Analysis with discovery (FDR_hit = TRUE) and progression 767 (FWER_hit = TRUE) for the Lung-Onc3_454 dataset (n=29)

768 Supplementary Table 10: BED file of SB insertions for HCA95_454

769 Supplementary Table 11: SB Driver Analysis with discovery (FDR_hit = TRUE) and progression 770 (FWER_hit = TRUE) for the HAC-Onc3_454 dataset (n=95)

771 Supplementary Table 12: Trunk SB Driver Analysis with discovery (FDR_hit = TRUE) and 772 progression (FWER_hit = TRUE) for the HAC-Onc3_454 dataset (n=95)

773 Supplementary Table 13: BED file of SB insertions for Liver-Onc2.3_SBC cohort

774 Supplementary Table 14: BED file of SB insertions for Other-Onc2.3_SBC cohort

775 Supplementary Table 15: BED file of SB insertions for Ovary-Onc2.3_SBC cohort

776 Supplementary Table 16: BED file of SB insertions for Onc2.3-Pan-Tumor-SBC27 cohort

Aiderus, Contreras, Meshey, et al., 2020 37 777 Supplementary Table 17: Discovery and progression SB Driver Analysis for Onc2.3-Pan-Tumor- 778 SBC27 cohort

779 Supplementary Table 18: Trunk SB Driver Analysis for Onc2.3-Pan-Tumor-SBC27. (Note: Six 780 trunk drivers — Aox2, Crlf3, Dgkd, Fgfr2, Ilf3, and Zfp292 — were manually removed from the 781 dataset because supporting evidence from three related lung masses from a single animal 782 provided insufficient evidence for tumor recurrence.)

783 Supplementary Table 19: Discovery and progression SB Driver Analysis for SB|Lung combined 784 Onc2.3 and Onc3 cohorts

785 Supplementary Table 20: COSMIC v91 Cancer Gene Census TSG enrichment with SB-Onc2.3 Pan- 786 tumor drivers

787 Supplementary Table 21: TSGdb enrichment with SB-Onc2.3 Pan-tumor drivers

788 Supplementary Table 22: Enrichr biological pathway and process analysis with SB-Onc2.3 Pan- 789 tumor drivers

790 Supplementary Table 23: Literature References summarizing studies that provide in vivo 791 evidence for validation of the TSGs identified

792 Supplementary Table 24: Rasgrf1 gene expression analysis of from SB-Onc3 Lung tumor 793 genomes

794 Acknowledgments

795 The authors wish to thank the Copeland–Jenkins labs in Singapore and Houston, the K. Mann Lab at 796 Moffitt Cancer Center and Martin McMahon and Aria Vaishnavi at Huntsman Cancer Institute for helpful 797 discussions; we thank Gail Martin (UCSF) for Actin-beta-Cre mice; the Institute for Molecular and Cell 798 Biology Histopathology Core; Adam Dupuy (Iowa) for providing the pT2/Onc2 plasmid; Holly Morris for 799 husbandry and Debra Householder for genotype assistance of the T2/Onc2.3 transgenic founder mouse 800 lines at NCI-Frederick (Frederick, MD, USA); Pearlyn Cheok, Nicole Lim, Dorothy Chen and Cherylin Wee 801 for assistance with tumor monitoring and animal husbandry and Keith Rogers and Susan M. Rogers for 802 assistance with necropsy and histotechnology services at IMCB (Singapore, Republic of Singapore); and 803 Bethanie Gore for assistance with animal husbandry at MCC/USF (Tampa, FL, USA). Transgenic founder 804 lines were created by the Mouse Cancer Genetics Program Transgenic Core Facility at NCI-Frederick. 805 Necropsy and histology was performed by the Advanced Molecular Pathology Laboratory, Institute of 806 Molecular and Cell Biology (A*STAR), Singapore and the Moffitt Tissue Core Facility. This work was 807 supported by the Center for Cancer Research, National Cancer Institute (D.S., N.G.C., and N.A.J.), 808 Biomedical Research Council, Agency for Science, Technology, and Research, Singapore (N.G.C. and N.A.J.), 809 Cancer Prevention Research Institute of Texas (N.G.C. and N.A.J.), Cancer Center Support Grant (CCSG 810 grant P30-CA76292) at the H. Lee Moffitt Cancer Center and Research Institute, a National Cancer 811 Institute-designated Comprehensive Cancer Center (K.M.M. and M.B.M), and the Moffitt Skin Cancer 812 SPORE (5P50CA168536-05) Career Enhancement Program Grant (M.B.M.).

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