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A functional taxonomy of tumor suppression in oncogenic KRAS-driven lung cancer

ABSTRACT: Extensive cancer genotyping has identified a large number of putative tumor suppressor genes. However, genome sequencing data alone is insufficient to uncover the importance or the specific functional roles of these genes during carcinogenesis. It is generally unclear whether more frequently mutated tumor suppressors are also more consequential for tumor development. Furthermore, whether tumor suppressors restrict the rate of tumor growth, decrease the probability of incipient tumorigenesis, or limit the emergence of particularly fast-growing clones remains unknown for even the most well-studied tumor suppressors. Here we use a multiplexed autochthonous mouse model of oncogenic Kras-driven human lung adenocarcinoma to quantify the impact of forty-eight known and putative tumor suppressor genes on diverse aspects of carcinogenesis at an unprecedented scale and resolution. We discover many previously understudied functional tumor suppressors that constrain multiple aspects of carcinogenesis in vivo. Inactivation of some genes substantially elevates tumor growth rate, while the inactivation of others increases the probability of tumor initiation and/or the emergence of exceptionally large tumors. While some known and novel functional tumor suppressor genes exert particularly strong effects during specific phases of tumorigenesis, others impact multiple facets of tumor development. These direct and causal analyses uncover an unexpectedly complex functional landscape of tumor suppression. This map of carcinogenesis has implications for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches to limit tumor initiation and progression.

ORGANISM(S): Mus musculus

PROVIDER: GSE146302 | GEO | 2021/02/04

REPOSITORIES: GEO

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Project description:Background: Epithelial-stromal crosstalk plays a critical role in invasive breast cancer (IBC) pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis. Results: We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive re-wiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, ER-positive IBC, and ER-negative IBC, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in IBC mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas. Conclusions: Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially-localized transcriptomic data. The analysis provides new biological insights into the re-wiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer. 36 flash-frozen human primary breast cancer samples were subjected to laser capture microdissection to separately isolate matched tumor epithelial and tumor-associated stromal components. RNA was isolated, subjected to 2 rounds of amplification, and hybridized on Agilent 4x44K microarrays along with a common reference (single round-amplified commercially obtained Universal Human Reference RNA) in a dyeswap design. For two samples of tumor-associated stroma, a second technical replicate was performed. Samples were labelled as ER-positive based on ESR1 gene expression levels in the tumor epithelium, using univariate Gaussian mixture model-based clustering via the mclust package in R.

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A functional taxonomy of tumor suppression in oncogenic KRAS-driven lung cancer

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