Developmental and Homeostatic origins of cancer

Division Of Basic Sciences - Nci

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Abstract

(1) Across cancers, tumor cells can resemble embryonic cell states that may allow them to metastasize and evade therapies. Melanoma is a cancer of the melanocyte that exhibits a wide range of transcriptional states characterized by alterations in embryonic melanocyte gene expression patterns. How these states and their functions are related to the embryonic precursors of melanocytes, the melanoblasts, is unknown. Here, we present the first high-resolution single-cell RNA-seq profiles of embryonic melanocytic lineages in mice. We discover a diverse array of transcriptional cell states in this lineage and confirm, for the first time at the single-cell level, that melanocytes arise from Schwann-cell precursors (SCPs), a highly plastic cell population, via a newly described intermediate mesenchymal-like state. Via novel computational strategies to map these developmental cell states to metastatic melanoma, we find that SCP-resembling tumors are associated with exclusion of the immune cells and non-response to immune checkpoint blockade. In contrast, a higher mesenchymal profile underlies immune dysfunction and resistance to BRAF-inhibition therapy. We also carry out the first time-resolved single-cell RNA-seq study of early melanoma metastatic colonization, demonstrating that melanoma cells activate a SCP program transiently during early metastatic colonization. Finally, we discover a hybrid lineage state that resembles multiple melanocytic lineages simultaneously and is enriched in melanoma cells during metastatic seeding and in therapy resistance. Our work reveals that the lineage-specific mechanisms underlie melanoma progression/evolution, including early metastatic colonization and therapeutic resistance. An earlier manuscript reporting this work is on BioRxiv. This work was submitted and rejected. During the last year, our collaborator have been performing several additional experiments. Most notably we identified HDac2 as a key regulator of hybrid state and have shown experimentally that HDACi sensitizes tumors to immunotherapy in mice. This work is anticipated to be submitted soon. (2) Characterizing the role of alternative splicing (AS) in cancer therapy response. We had demonstrated for the first time a broad recapitulation of developmental splicing patterns in multiple cancers, and additionally identified key upstream splicing factors, as well as transcription factors likely mediating the global splicing changes. Our results strongly support a model for a global switch in the transcriptional programs likely mediated by a few upstream transcriptional and splicing regulators. Combined with additional evidence showing and association between stem-like cellular states and therapy resistance, we hypothesize that, mediated by similar upstream regulatory mechanisms as in development and oncogenesis, the global changes in the AS profile may also be associated with therapy resistance. We are currently analyzing AS associated with drug response to BRAFi therapy in melanoma. This work is being done in collaboration with the Ruppin lab and Ze'ev Ronai at Cedar Sinai cancer center. We have provided several candidates that ROnai lab is currently testing in cell line models. (3) Similarities between oncogenesis and several homeostatic processes (HP) - wound healing, regeneration, and cellular stress response, have long been recognized. However, the molecular underpinning of these similarities is not fully understood. While several molecular aspects of HP are evolutionarily conserved, different species exhibit substantial variation in the genes involved in these HP as well as predisposition to cancer. Leveraging 75 published experimental datasets of genes implicated in HP across multiple species, we comprehensively investigate links between conserved aspects of HP and human cancers. We find that across cancer types, HP genes are significantly perturbed, both mutationally and transcriptionally, and associated with patient survival. In the human protein interaction network, HP genes cluster by the process type as well as with the known cancer driver genes. We present a tool - UNITe, which predicts cancer drivers based solely on network-proximity to HP genes, with an auROC of 0.81, and reveals novel potential cancer drivers exhibiting several expected features of known cancer drivers. Overall, we present a first comparative analysis of cancer drivers with conserved homeostatic processes, suggesting a complementary approach to prioritize cancer drivers. This work is complete. However, the first author had moved on to grad school had become non-responsive. We have recruited another collaborator Dr. Piyush Agrawal to lead and finish this work, which we anticipate submitted in a few weeks.