Highlights d Alveolar epithelial progenitor cells are transcriptionally distinct upon KRAS expression d Alveolar epithelial organoids recapitulate early-stage lung adenocarcinoma d Oncogenic KRAS leads to loss of lineage identity in AT2 cells d Bulk, scRNA-seq, and proteomics data from murine and human KRAS mutant AT2 cells

The mammalian Hippo signaling pathway, through its effectors YAP and TAZ, coerces epithelial progenitor cell expansion for appropriate tissue development or regeneration upon damage. Its ability to drive rapid tissue growth explains why many oncogenic events frequently exploit this pathway to promote cancer phenotypes. Indeed, several tumor types including basal cell carcinoma (BCC) show genetic aberrations in the Hippo (or YAP/TAZ) regulators. Here, we uncover that while YAP is dispensable for homeostatic epidermal regeneration, it is required for BCC development. Our clonal analyses further demonstrate that the few emerging Yap-null dysplasia have lower fitness and thus are diminished as they progress to invasive BCC Mechanistically, YAP depletion in BCC tumors leads to effective impairment of the JNK-JUN signaling, a well-established tumor-driving cascade. Importantly, in this context, YAP does not influence canonical Wnt or Hedgehog signaling. Overall, we reveal Hippo signaling as an independent promoter of BCC pathogenesis and thereby a viable target for drug-resistant BCC.

Transcription factor networks shape the gene expression programs responsible for normal cell identity and pathogenic state. Using Core Regulatory Circuitry analysis (CRC), we identify PAX8 as a candidate oncogene in Renal Cell Carcinoma (RCC) cells. Validation of large-scale functional genomic screens confirms that PAX8 silencing leads to decreased proliferation of RCC cell lines. Epigenomic analyses of PAX8-dependent cistrome demonstrate that PAX8 largely occupies active enhancer elements controlling genes involved in various metabolic pathways. We selected the ferroxidase Ceruloplasmin (CP) as an exemplary gene to dissect PAX8 molecular functions. PAX8 recruits histone acetylation activity at bound enhancers looping onto the CP promoter. Importantly, CP expression correlates with sensitivity to PAX8 silencing and identifies a subset of RCC cases with poor survival. Our data identifies PAX8 as a candidate oncogene in RCC and provides a potential biomarker to monitor its activity.

Epigenetic regulators are attractive anticancer targets, but the promise of therapeutic strategies inhibiting some of these factors has not been proven in vivo or taken into account tumor cell heterogeneity. Here we show that the histone methyltransferase G9a, reported to be a therapeutic target in many cancers, is a suppressor of aggressive lung tumor-propagating cells (TPCs). Inhibition of G9a drives lung adenocarcinoma cells towards the TPC phenotype by de-repressing genes which regulate the extracellular matrix. Depletion of G9a during tumorigenesis enriches tumors in TPCs and accelerates disease progression metastasis. Depleting histone demethylases represses G9a-regulated genes and TPC phenotypes. Demethylase inhibition impairs lung adenocarcinoma progression in vivo. Therefore, inhibition of G9a is dangerous in certain cancer contexts, and targeting the histone demethylases is a more suitable approach for lung cancer treatment. Understanding cellular context and specific tumor populations is critical when targeting epigenetic regulators in cancer for future therapeutic development.

Lung Cancer is the leading cause of cancer-related deaths worldwide. This is mainly due to late diagnosis and therefore advanced stage of the disease. Understanding the cell of origin of cancer and the processes that lead to its transformation will allow for earlier diagnosis and more accurate prediction of tumour type, ultimately leading to better treatments and lower patient morbidity. In this review, we focus on alveolar type 2 (AT2) cells as the cell of origin of lung adenocarcinoma (LUAD), the most common type of lung cancer. We first elaborate on the different oncogenes that are associated with LUAD and other lung cancers. After, we lay out in detail what is known about AT2 biology, to further delve into AT2 cells as cell of origin for adenocarcinoma. Understanding the precursors of LUAD and identifying the molecular changes during its progression will allow for earlier detection and better molecular targeting of the disease in early stages.

Neuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors and poorly-differentiated carcinomas. Treatment options for patients with NENs are limited, in part due to lack of accurate models. To address this need we established the first patient-derived tumor organoids (PDTOs) from pulmonary neuroendocrine tumors and derived PDTOs from an understudied NEN subtype, large cell neuroendocrine carcinoma (LCNEC). PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through drug sensitivity analyses, we uncover therapeutic sensitivities to an inhibitor of NAD salvage biosynthesis and to an inhibitor of BCL-2. Finally, we identify a dependency on EGF in pulmonary neuroendocrine tumor PDTOs. Consistent with these findings, analysis of an independent cohort showed that approximately 50% of pulmonary neuroendocrine tumors expressed EGFR. This study identifies a potentially actionable vulnerability for a subset of NENs, and further highlights the utility of these novel PDTO models for the study of NENs.

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Traditional therapeutic approaches such as chemotherapy or radiotherapy have provided only a marginal improvement in the treatment of lung carcinomas. Inhibitors targeting specific genetic aberrations present in non-small cell lung cancer (NSCLC), the most common subtype (85%), have improved the prognostic outlook, but due to the complexity of the LC mutational spectrum, only a fraction of patients benefit from these targeted molecular therapies. More recently, the realization that the immune infiltrate surrounding solid tumors can foster tumor-promoting inflammation has led to the development and implementation of anticancer immunotherapies in the clinic. In NSCLC, one of the most abundant leukocyte infiltrates is macrophages. These highly plastic phagocytes, which are part of the cellular repertoire of the innate immunity, can have a pivotal role in early NSCLC establishment, malignant progression, and tumor invasion. Emerging macrophage-targeting therapies have been focused on the re-differentiation of the macrophages toward an antitumorigenic phenotype, depletion of tumor-promoting macrophage subtypes, or combination therapies combining traditional cytotoxic treatments with immunotherapeutic agents. The most extensively used models employed for the exploration of NSCLC biology and therapy have been 2D cell lines and murine models. However, studying cancer immunology requires appropriately complex models. 3D platforms, including organoid models, are quickly advancing powerful tools to study immune cell-epithelial cell interactions within the tumor microenvironment. Co-cultures of immune cells along with NSCLC organoids allow for an in vitro observation of the tumor microenvironment dynamics closely resembling in vivo settings. Ultimately, the implementation of 3D organoid technology into tumor microenvironment-modeling platforms might facilitate the exploration of macrophage-targeted therapies in NSCLC immunotherapeutic research, thus establishing a new frontier in NSCLC treatment.

We here present COOBoostR (https://github.com/SWJ9385/COOBoostR), a computational method designed for the putative prediction of tissue- or cell-of-origin of various cancer types. COOBoostR leverages regional somatic mutation density information and chromatin mark features to be applied to an extreme gradient boosting-based machine-learning algorithm. COOBoostR ranks chromatin marks from various tissue and cell types which best explain the somatic mutation density landscape of any sample of interest. Through integrating either ChIP-seq based chromatin data or bulk/single cell chromatin accessibility data along with regional somatic mutation density data derived from normal cells/tissue, precancerous lesions, and cancer types, we show that COOBoostR outperforms existing random forest-based methods in prediction speed with comparable or better tissue or cell-of-origin prediction performance. In addition, our results suggest a dynamic somatic mutation accumulation at the normal tissue or cell stage which could be intertwined with the changes in open chromatin marks and enhancer sites. These results further represent chromatin marks shaping the somatic mutation landscape at the early stage of mutation accumulation, possibly even before the initiation of precancerous lesions or neoplasia.