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Human breast cancer (BRCA) shows tremendous genomic, gene expression, clinical, and phenotypic heterogeneity. Known driver gene alterations can only explain a portion of this heterogeneity, some of which likely arise from variation in the target cell for transformation, in addition to incompletely understood gene copy number and epigenetic alterations. These factors are difficult to identify with certainty using human patient samples due to widely varying germline genetic backgrounds, thousands of gene copy and epigenetic changes per sample, and, unknown target cell transformation. Activating mutations in the p110α catalytic subunit of PI3K are one of the most common genetic alterations in human BRCA. Here, we report results from two Sleeping Beauty (SB) transposon-accelerated mouse models of Pik3ca-mutant mammary cancer showing how genotype-phenotype correlations can be drawn providing strong candidates for mediating tumor phenotypes, including estrogen-receptor (ER)-dependent gene expression, high cell cycle activity, and immune cell exclusion. We used SB transposon mutagenesis in mice on a Pik3caH1047R activated mutant background to model mammary cancer development in two different mammary epithelial compartments. Both the target cell for mutagenesis and the specific transposon-induced mutations correlated with specific tumor phenotypes, including whether the tumors were ER positive or negative. RNA sequencing of tumors revealed novel genotype-phenotype correlations implicating specific transposon-altered gene drivers of high cell cycle activity, ER-dependent gene expression, and white blood cell exclusion from the tumor. Many transposon-implicated genes are altered at the gene copy number or epigenetic/methylation level in human BRCA, and several were functionally validated. These models provide a source of genetically heterogenous mouse mammary tumors with a uniform initiating mutation, Pik3caH1047R, useful for identifying cooperating pathways and drivers of specific tumor phenotypes. Citation Format: Morito Kurata, Emiily Pope, Jingmin Shu, Wenlin Yuan, Wendy Hudson, Mark Sokolowski, Setareh Bagherzadeh, Zora Modrusan, Eric Stawiski, Steffen Durinck, Sekar Seshigiri, Aaron Sarver, Nuri Temiz, David Largaespada. Discovery of cancer genes and pathways operative in PI3K-activated mammary cancer reveals clinically relevant genotype-phenotype correlations. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-04.

Supplementary Table S3 - PDF file 39K, Computational prediction of miR-142-3p target mRNA

PDF file - 67K, Gene list corresponding to the heapmap in Figure 2C.

PDF file - 166K, Bortezomib death profiles of mouse and human plasma cell lines for gene expression profiling.

Supplementary Figure 1 - PDF file 33K, Principle components analysis

PDF file - 67K, Full drug table of CMAP predictions corresponding to Figure 2.

PDF file - 59K, Unique gene predictors of the panobinostat response in bortezomib-resistant mouse cell lines.

PDF file - 76K

PDF file - 44K, Gene list corresponding to the heatmap in Figure 1B.

Supplementary Figure 2 - PDF file 156K, Validation of miRNA microarray by real-time PCR

Supplementary Legends - PDF file 81K, Supplementary figure legends and supplementary table legends

PDF file - 1297K, Quantitative RT-PCR and histologic analysis of differences between sensitive and resistant mouse cell lines.

Supplementary Figure 3 - PDF file 49K, Effect of triptolide on miRNAs known to play a role in PDAC

Supplementary Figure 5 - PDF file 62K, HSF1 and miR-142-3p independently regulate HSPA1B (HSP70) and mediate triptolide-induced suppression of PDAC proliferation

PDF file - 143K, Gene set enrichment analysis of mouse and human cell lines.

PDF file - 463K, Proteasome activity and baseline gene expression differences between sensitive and resistant mouse cell lines.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of neoplastic plasma cells in the bone marrow. Although the first-to-market proteasome inhibitor bortezomib (Velcade) has been successfully used to treat patients with myeloma, drug resistance remains an emerging problem. In this study, we identify signatures of bortezomib sensitivity and resistance by gene expression profiling (GEP) using pairs of bortezomib-sensitive (BzS) and bortezomib-resistant (BzR) cell lines created from the Bcl-XL/Myc double-transgenic mouse model of multiple myeloma. Notably, these BzR cell lines show cross-resistance to the next-generation proteasome inhibitors, MLN2238 and carfilzomib (Kyprolis) but not to other antimyeloma drugs. We further characterized the response to bortezomib using the Connectivity Map database, revealing a differential response between these cell lines to histone deacetylase (HDAC) inhibitors. Furthermore, in vivo experiments using the HDAC inhibitor panobinostat confirmed that the predicted responder showed increased sensitivity to HDAC inhibitors in the BzR line. These findings show that GEP may be used to document bortezomib resistance in myeloma cells and predict individual sensitivity to other drug classes. Finally, these data reveal complex heterogeneity within multiple myeloma and suggest that resistance to one drug class reprograms resistant clones for increased sensitivity to a distinct class of drugs. This study represents an important next step in translating pharmacogenomic profiling and may be useful for understanding personalized pharmacotherapy for patients with multiple myeloma. Mol Cancer Ther; 12(6); 1140–50. ©2013 AACR.

Supplementary Figure 4 - PDF file 31K, Effect of microRNA-142-3p mimic overexpression on HSPA1A (HSP70) levels

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest malignancies, is resistant to current chemotherapies. We previously showed that triptolide inhibits PDAC cell growth in vitro and blocks metastatic spread in vivo. Triptolide downregulates HSP70, a molecular chaperone upregulated in several tumor types. This study investigates the mechanism by which triptolide inhibits HSP70. Because microRNAs (miRNA) are becoming increasingly recognized as negative regulators of gene expression, we tested whether triptolide regulates HSP70 via miRNAs. Here, we show that triptolide as well as quercetin, but not gemcitabine, upregulated miR-142-3p in PDAC cells (MIA PaCa-2, Capan-1, and S2-013). Ectopic expression of miR-142-3p inhibited cell proliferation, measured by electric cell-substrate impedance sensing, and decreased HSP70 expression, measured by real-time PCR and immunoblotting, compared with controls. We showed that miR-142-3p directly binds to the 3′UTR of HSP70, and that this interaction is important as HSP70 overexpression rescued miR–142-3p-induced cell death. We found that miR–142-3p regulates HSP70 independently of heat shock factor 1. Furthermore, Minnelide, a water-soluble prodrug of triptolide, induced the expression of miR-142-3p in vivo. This is the first description of an miRNA-mediated mechanism of HSP70 regulation in cancer, making miR-142-3p an attractive target for PDAC therapeutic intervention. Mol Cancer Ther; 12(7); 1266–75. ©2013 AACR.

This review will describe more than two decades of comparative research on primary bone cancer (osteosarcoma). Osteosarcoma is a chaotic disease present in a complex and variable microenvironment composed of many different cell types which interact with each other and lead to high transcriptional heterogeneity. Despite this heterogeneity, common transcriptional patterns can be observed in the bulk transcriptomes of these tumors; additionally, these patterns are associated with outcome, indicating their importance to the molecular biology of the disease. Work from our group and others has led to our current understanding of osteosarcoma as a disease where multiple pathological processes appear to converge into a limited array of tissue organizations with distinct biology. Recurrent as well as distinct events can lead to these states of tissue organization, explaining the heterogeneity of osteosarcoma that is observed among and within species. Yet, despite their chaotic genomes, osteosarcomas seem to be (relatively) genetically stable, with persistent maintenance of essentially the same chromothriptic karyotype throughout the developmental lifetime of the tumor. Importantly, the transcriptional variance between tumors can highlight the underlying biology of the malignant cells themselves, as well as the composition of the osteosarcoma microenvironment and the host response, both of which are prognostically significant for this disease. Initial single cell RNA-seq reports provide further evidence of the importance of the osteosarcoma microenvironment for tumor characterization. Our data suggest that improving patient outcomes in immunologically barren or “cold” osteosarcomas, necessitates generating immune permissive or “warmer” microenvironments within the tumor. Furthermore, the aging bone microenvironment may create specific niches that predispose to cancer, and identification of the drivers that lead to these variable transcriptional patterns will be essential to identify personalized, effective genomic therapy for osteosarcoma.

11525 Background: Osteosarcoma (OS) incidence is characterized by a bimodal age distribution, with peaks in early adolescence and in adults > 65 years of age. In contrast to adolescents, OS in adults is frequently considered as a secondary neoplasm (i.e., transformation of Paget´s disease of the bone, radiation induced). Yet, the literature is scarce regarding the impact of age on the molecular landscape of OS. Herein, we sought to explore the association between age and the genomic profile as well as the tumor immune microenvironment (TME) in a large cohort of OS patients. Methods: 208 specimens were centrally analysed at the Caris Life Sciences laboratory with DNA seq (NextSeq, 592 gene panel or NovaSeq, whole-exome sequencing), RNA seq (Archer fusion panel or whole-transcriptome sequencing) and immunohistochemistry (IHC). RNA deconvolution and differential expression analyses were performed using the Microenvironment Cell Populations counter method for quantification of immune cell populations and gene expression profiling. The cohort was stratified into three distinct age groups (< 25 years [n = 83], 25-45 years [n = 58], > 45 years [67]). Results: Overall, the most frequently detected mutations were in TP53 (37%), RB1 (13%), ATRX (9%), TERT (6%), PTEN (5%), PIK3CA (4%) and KMT2D (3%). Copy number alterations were most frequently detected in CDK4 (12%), LRIG3 (11%), FLCN (11%), MDM2 (9%), CCND3 (9%), VEGFA (8%), TFEB (8%). Interestingly, age-based stratification revealed an increased frequency of FLCN (19.7 vs 4.7%, p < 0.01), CCND3 (13.9 vs 3.1%, p < 0.05), and HSP90AB1 (11.3 vs 0.0%, p < 0.01), alterations in patients < 25 years compared to > 45 years. TME analysis revealed that patients > 45 years have decreased B-cell abundance compared to patients < 25 years (2.9-fold decrease, p < 0.05) and 25-45 years (4.8-fold decrease, p < 0.05). Although not statistically significant, median transcriptional expression of PD-L1 was numerically increased in patients > 45 years (1.8-fold compared to 25-45 years, p = 0.17; 2.0-fold compared to < 25 years, p = 0.27), which was consistent with increasing rates of IHC PD-L1 expression with age (5.3%, 9.4%, and 17.5%, respectively, p = 0.06). Conclusions: To the best of our knowledge, this study represents the largest cohort of molecularly characterized OS. Age-associated differences in the genetic landscape and TME composition, including increased gene amplifications observed in younger patients and decreased B-cell abundance in older patients, might suggest fundamental underlying molecular and biological differences.

Forward genetic insertional mutagenesis screens are used by many labs to identify candidate cancer genes. We and others have used the Sleeping Beauty DNA transposon to generate random mutations within the murine genome that cause cancer. Identification of the insertion sites, either via RNA sequencing or DNA sequencing, is required for cancer gene discovery. Multiple sequencing-based approaches have been utilized to identify locations of transposon insertions within a genome including linker-mediated PCR, RNA-Seq, and Seq capture. Here, a bioinformatics pipeline is presented applicable to both the identification of transposon-generated fusions in RNA-Seq data and the direct identification of transposon insertion sites in DNA sequencing data. We are currently utilizing this method to identify transposon insertions generated by Sleeping Beauty transposase-mediated mobilization of the T2/Onc transposon within the murine genome. With slight modification, this approach is amenable to the identification of any mobile genetic element within any genome.

The transcription factors EBF1 and PAX5 are frequently mutated in B cell acute lymphoblastic leukemia (B-ALL). We demonstrated that Pax5+/− x Ebf1+/− compound heterozygous mice develop leukemia with high penetrance. Similar results were seen in Pax5+/− x Ikzf1+/− and Ebf1+/− x Ikzf1+/− mice for B-ALL, or in Tcf1+/− x Ikzf1+/− mice for T cell leukemia. To identify genetic defects that cooperate with Pax5 and Ebf1 compound heterozygosity to initiate leukemia, we carried out a Sleeping Beauty transposon screen. This screen identified a number of cooperating partners including gain-of-function mutations in Stat5 (~65%) and Jak1(~68%), as well as loss-of-function mutations in Cblb (61%)and Myb (32%). These findings highlight the key role of JAK/STAT5 signaling in cooperating with Pax5 and Ebf1 compound haploinsufficiency to drive B cell transformation. Moreover, these studies pointed to unexpected roles for loss of function mutations in CBL-b and MYB in B cell transformation. Subsequent RNA-Seq studies on WT, Pax5+/−, Ebf1+/−, Pax5+/− x Ebf1+/− pre-leukemic, Pax5+/− x Ebf1+/− leukemic cells and Pax5+/− x Ebf1+/− Sleeping Beauty leukemic cells demonstrated upregulation of a PDK1>PLK1>MYC pathway; treatment of Pax5+/− x Ebf1+/− leukemias with PDK1 specific inhibitors blocked their proliferation in vitro. Finally, we identified conserved transcriptional variation in a subset of genes between human leukemias and our mouse B-ALL models. Thus, compound haploinsufficiency for B cell transcription factors likely plays a critical role in transformation of human B cells and suggest that newly developed PDK1 inhibitors may be effective for treating patients characterized by such defects.